Traffic accident energy loss estimation using three-dimensional computer vision

ilustraciones, fotografías, graficas

Autores:
Toquica, Hans
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
eng
OAI Identifier:
oai:repositorio.unal.edu.co:unal/81041
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/81041
https://repositorio.unal.edu.co/
Palabra clave:
000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computación
Energy loss estimation
Energy equivalent speed
Traffic accident reconstruction
Structure from motion
Photogrammetry
Estimación de pérdida de energía
Reconstrucción de accidentes de tránsito
Fotogrametría
Fotogrametría
Reconocimiento topográfico
Photogrammetry
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_e342fdd2b5872e43751ceb81764b0f88
oai_identifier_str oai:repositorio.unal.edu.co:unal/81041
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.eng.fl_str_mv Traffic accident energy loss estimation using three-dimensional computer vision
dc.title.translated.spa.fl_str_mv Estimación de pérdida de energía en accidentes de tránsito usando visión tridimensional
title Traffic accident energy loss estimation using three-dimensional computer vision
spellingShingle Traffic accident energy loss estimation using three-dimensional computer vision
000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computación
Energy loss estimation
Energy equivalent speed
Traffic accident reconstruction
Structure from motion
Photogrammetry
Estimación de pérdida de energía
Reconstrucción de accidentes de tránsito
Fotogrametría
Fotogrametría
Reconocimiento topográfico
Photogrammetry
title_short Traffic accident energy loss estimation using three-dimensional computer vision
title_full Traffic accident energy loss estimation using three-dimensional computer vision
title_fullStr Traffic accident energy loss estimation using three-dimensional computer vision
title_full_unstemmed Traffic accident energy loss estimation using three-dimensional computer vision
title_sort Traffic accident energy loss estimation using three-dimensional computer vision
dc.creator.fl_str_mv Toquica, Hans
dc.contributor.advisor.none.fl_str_mv Prieto Ortiz, Flavio Augusto
dc.contributor.author.none.fl_str_mv Toquica, Hans
dc.subject.ddc.spa.fl_str_mv 000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computación
topic 000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computación
Energy loss estimation
Energy equivalent speed
Traffic accident reconstruction
Structure from motion
Photogrammetry
Estimación de pérdida de energía
Reconstrucción de accidentes de tránsito
Fotogrametría
Fotogrametría
Reconocimiento topográfico
Photogrammetry
dc.subject.proposal.eng.fl_str_mv Energy loss estimation
Energy equivalent speed
Traffic accident reconstruction
Structure from motion
Photogrammetry
dc.subject.proposal.spa.fl_str_mv Estimación de pérdida de energía
Reconstrucción de accidentes de tránsito
Fotogrametría
dc.subject.unesco.spa.fl_str_mv Fotogrametría
Reconocimiento topográfico
dc.subject.unesco.eng.fl_str_mv Photogrammetry
description ilustraciones, fotografías, graficas
publishDate 2021
dc.date.issued.none.fl_str_mv 2021-09
dc.date.accessioned.none.fl_str_mv 2022-02-22T21:24:51Z
dc.date.available.none.fl_str_mv 2022-02-22T21:24:51Z
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/81041
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/81041
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv J. F. Kerkhoff, “Photographic techniques for accident reconstruction,” SAE Transactions, vol. 94, pp. 292–305, 1985, ISSN: 0096736X. [Online]. Available: http://www.jstor.org/stable/44467584.
H. Xu and G. Lu, “Application of photogrammetry to measurement of traffic accident scene,” Traffic and Transportation Studies, 2002.
L. Zhang, W. H. Qin, T. J. He, and W. N. Li, “Special considerations for tdoa application to the reconstruction of traffic accidents,” Advanced Materials Research, vol. 255-260, pp. 4090–4094, 2011. DOI: 10.4028/www.scientific.net/amr.255-260.4090.
M. Pepe, J. Sobek, and G. Huett, “Three dimensional computerized photogrammetry and its application to accident reconstruction,” International Congress and Exposition Motor Vehicle Accident Reconstruction:, 1989.
D. Behring, J. Thesing, H. Becker, and R. Zobel, “Optical coordinate measuring techniques for the determination and visualization of 3d displacements in crash investigations,” Society of Automotive Engineers, 2001.
K. Breen and C. Anderson, “The application of photogrammetry to accident reconstruction,” Society of Automotive Engineers, 1986.
B. Dierckx, C. De Veuster, and P.-A. Guidault, “Measuring a geometry by photogrammetry: Evaluation of the approach in view of experimental modal analysis on automotive structures,” Proceedings of the 2001 Noise and Vibration Conference, 2020.
E. J. Manuel, R. Mink, and D. Kruger, “Videogrammetry in vehicle crash reconstruction with a moving video camera,” SAE Technical Paper Series, 2018. DOI: 10.4271/2018-01-0532.
P. Niederer, B. Birchler, F. Mesqui, and Y. Lehareinger, “Computer assisted single-view photogrammetry for accident scene documentation,” SAE International, 1985.
M. R. Osman and K. N. Tahar, “3d accident reconstruction using low-cost imaging technique,” Advances in Engineering Software, vol. 100, pp. 231–237, 2016. DOI: 10 . 1016 / j .advengsoft.2016.07.007.
L. Pádua, J. Sousa, J. Vanko, J. Hruška, T. Adão, E. Peres, A. Sousa, and J. J. Sousa, “Digital reconstitution of road traffic accidents: A flexible methodology relying on uav surveying and complementary strategies to support multiple scenarios,” International Journal of Environmental Research and Public Health, vol. 17, no. 6, p. 1868, 2020. DOI: 10.3390/ijerph17061868.
B. Randles, B. Jones, J. Welcher, T. Szabo, D. Elliott, and C. MacAdams, “The accuracy of photogrammetry vs. hands-on measurement techniques used in accident reconstruction,” SAE International, 2010.
T. Terpstra, T. Voitel, and A. Hashemian, “A survey of multi-view photogrammetry software for documenting vehicle crush,” SAE Technical Paper Series, 2016. DOI: 10.4271/2016- 01-1475.
X. Du, X. Jin, X. Zhang, J. Shen, and X. Hou, “Geometry features measurement of traffic accident for reconstruction based on close-range photogrammetry,” Advances in Engineering Software, vol. 40, no. 7, pp. 497–505, 2009. DOI: 10.1016/j.advengsoft.2008.09.002.
I. Han and H. Kang, “Three-dimensional crush scanning methods for reconstruction of vehicle collision accidents,” International Journal of Automotive Technology, vol. 17, no. 1, pp. 91–98, 2016. DOI: 10.1007/s12239-016-0008-y.
K. L. Campbell, “Energy basis for collision severity,” SAE Transactions, vol. 83, pp. 2114–2126, 1974, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44657484.
United States. National Highway Traffic Safety Administration. Accident Investigation Division, CRASH3 User’s Guide and Technical Manual. The Division, 1981. [Online]. Available: https://books.google.com.co/books?id=tv85AQAAMAAJ.
R. A. Smith and J. T. Noga, “Accuracy and sensitivity of crash,” SAE Technical Paper Series, 1982. DOI: 10.4271/821169.
R. L. Woolley, C. Y. Warner, and M. D. Tagg, “Inaccuracies in the crash3 program,” SAE Transactions, vol. 94, pp. 380–398, 1985, ISSN: 0096736X. [Online]. Available: http://www.jstor.org/stable/44467589.
B. McHenry, “The algorithm of CRASH,” United States: McHenry Software, Inc., 2001.
A. G. Fonda, “Principles of crush energy determination,” SAE Transactions, vol. 108, pp. 392–406, 1999, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44667911.
D. Vangi, “Energy loss in vehicle to vehicle oblique impact,” International Journal of Impact Engineering, vol. 36, no. 3, pp. 512–521, 2009. DOI: 10.1016/j.ijimpeng.2008.09.001.
M. Gidlewski, L. Prochowski, L. Jemioł, and D. Żardecki, “The process of front-to-side collision of motor vehicles in terms of energy balance,” Nonlinear Dynamics, vol. 97, no. 3, pp. 1877–1893, 2018. DOI: 10.1007/s11071-018-4688-x.
G. A. Nystrom, G. Kost, and S. M. Werner, “Stiffness parameters for vehicle collision analysis,” SAE Transactions, vol. 100, pp. 169–176, 1991, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44632021.
J. A. Neptune, G. Y. Blair, and J. E. Flynn, “A method for quantifying vehicle crush stiffness coefficients,” SAE Technical Paper Series, 1992. DOI: 10.4271/920607.
A. R. Várkonyi-kóczy, A. Rövid, and P. Várlaki, “Intelligent methods for car deformation modeling and crash speed estimation,” 2004.
I. Han and H. Kang, “Determination of the collision speed of a vehicle from evaluation of the crush volume using photographs,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 230, no. 4, pp. 479–490, 2015. DOI: 10.1177/0954407015586906.
J. Goicolea, “Estructuras sometidas a impacto,” 2000.
R. Burdzik, P. Folega, L. Konieczny, B. Lazarz, Z. Stanik, and J. Warczek, “Analysis of material deformation work measures in determination of a vehicle’s collision speed,” Archives of Materials Science and Engineering, 2020.
F. Berg, F. Walz, M. Muser, H. Bürkle, and J. Epple, “Implications of Velocity Change Delta-V and Energy Equivalent Speed EES for Injury Mechanism Assesment in Various Colission Configurations,” IRCOBI Conference - Göteborg, 1998.
G. Păduraru, “Vehicle speed correlation with deformation amplitude due to adult pedestrian impact in car traffic accidents,” Ovidius University Annals of Mechanical, Industrial and Maritime Engineering, 2008.
A. Toglia, G. Stephens, D. Michalski, and J. Rodriguez, “Applications of photomodeler in accident reconstruction,” 2005 ASME International Mechanical Engineering Congress and Exposition, 2005.
C. Fraser, “Accident reconstruction via digital close-range photogrammetry,” 2006.
A. Morales, D. Gonzalez-Aguilera, M. Gutiérrez, and A. López, “Energy analysis of road accidents based on close-range photogrammetry,” Remote Sensing, vol. 7, no. 11, pp. 15 161–15 178, 2015. DOI: 10.3390/rs71115161.
D. A. Jurkofsky, “Accuracy of suas photogrammetry for use in accident scene diagramming,” SAE International Journal of Transportation Safety, vol. 3, no. 2, pp. 136–152, 2015. DOI: 10 .4271/2015-01-1426.
Z. Bo, X. Haitao, L. Lulu, J. Jun, Z. Jianyue, and T. Yiping, “Development of coordinate-machine of the scene of road traffic accident based on binocular stereo omni-directional vision sensors,” Procedia Engineering, vol. 24, pp. 262–266, 2011. DOI: 10.1016/j.proeng.2011.11.2638.
F. Mesqui, P. Niederer, M. Schlumpf, Y. Lehareinger, and J. Walton, “Semi-automatic reconstruction of the spatial trajectory of an impacted pedestrian surrogate using high-speed cinephotogrammetry and digital image analysis,” Journal of Biomechanical Engineering, vol. 106, no. 4, pp. 357–359, 1984. DOI: 10.1115/1.3138505.
V. Žuraulis, L. Levulytė, and E. Sokolovskij, “Vehicle speed prediction from yaw marks using photogrammetry of image of traffic accident scene,” Procedia Engineering, vol. 134, pp. 89–94, 2016. DOI: 10.1016/j.proeng.2016.01.043.
B. Epstein and B. G. Westlake, “Determination of vehicle speed from recorded video using reverse projection photogrammetry and file metadata,” Journal of Forensic Sciences, vol. 64, no. 5, pp. 1523–1529, 2019. DOI: 10.1111/1556-4029.14053.
D. F. Tandy, C. Coleman, J. Colborn, T. Hoover, and J. Bae, “Benefits and methodology for dimensioning a vehicle using a 3d scanner for accident reconstruction purposes,” SAE Technical Paper Series, 2012. DOI: 10.4271/2012-01-0617.
J. Arnold, H. Bösch, and M. Braun, “Reconstruction of a multi vehicle collision on a highway: Combining forensic evidence examination, 3d-scanning and 3d-photogrammetry with numerical accident reconstruction methods,” IRCOBI Conference - Bern (Switzerland), 2008.
L. Barazzetti, R. Sala, M. Scaioni, C. Cattaneo, D. Gibelli, A. Giussani, P. Poppa, F. Roncoroni, and A. Vandone, “3d scanning and imaging for quick documentation of crime and accident scenes,” Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI, 2012. DOI: 10.1117/12.920728.
U. Buck, K. Buße, L. Campana, F. Gummel, C. Schyma, and C. Jackowski, “What happened before the run over? morphometric 3d reconstruction,” Forensic Science International, vol. 306, p. 110 059, 2020. DOI: 10.1016/j.forsciint.2019.110059.
U. Buck, S. Naether, M. Braun, S. Bolliger, H. Friederich, C. Jackowski, E. Aghayev, A. Christe, P. Vock, and R. Dirnhofer, “Application of 3d documentation and geometric reconstruction methods in traffic accident analysis: With high resolution surface scanning, radiological msct/mri scanning and real data based animation,” Forensic Science International, vol. 170, no. 1, pp. 20–28, 2007. DOI: 10.1016/j.forsciint.2006.08.024.
W. Baier, M. J. Donnelly, M. Payne, and M. A. Williams, “A holistic multi-scale approach to using 3d scanning technology in accident reconstruction,” Journal of Forensic Sciences, vol. 65, no. 5, pp. 1774–1778, 2020. DOI: 10.1111/1556-4029.14405.
U. Buck, S. Naether, B. Räss, C. Jackowski, and M. J. Thali, “Accident or homicide - virtual crime scene reconstruction using 3d methods,” Forensic Science International, vol. 225, no. 1-3, pp. 75–84, 2013. DOI: 10.1016/j.forsciint.2012.05.015.
C. Strother, R. Kent, and C. Warner, “Estimating vehicle deformation energy for vehicles struck in the side,” Advances in Safety Technology, 1998.
N. Carter, A. Hashemian, N. Rose, and W. Neale, “Evaluation of the accuracy of image based scanning as a basis for photogrammetric reconstruction of physical evidence,” SAE International, 2020.
William Kevin Peach v. Lynsey E. McGovern. Supreme Court of the State of Illinois No:123156, 2018.
R. Fay, “Analytical applications of 3-d imaging in vehicle accident studies,” Accident Reconstruction: Technology and Animation VI, 1996.
D. Rudny and D. Sallmann, “The use of electronic survey equipment in the creation of accident scene diagrams,” Accident Reconstruction: Technology and Animation V, 1995.
H. Toquica, “Estado de arte: Visión de máquina y técnicas de inteligencia artificial para la deteccion de infracciones de tránsito por alta velocidad,” Humanities Commons, 2020. DOI:10.17613/81qy-1r28.
Siniestros en las vías, un problema de salud pública, El Tiempo, Feb. 2018. [Online]. Available: https://www.eltiempo.com/salud/informe-de-la-oms-sobre-accidentes-de-transito-en-el-mundo-302888 (visited on 05/01/2020).
N. Tumbas, R. Kinney, and G. Smith, “Photogrammetry and accident reconstruction: Experimental results,” Accident Reconstruction: Technology and Animation IV, 1994.
R. Hernández Sampieri, C. Fernández Collado, and M. d. P. Baptista Lucio, Metodología de la investigación (5a. ed.) McGraw-Hill Interamericana, 2000.
G. Agudelo, M. Aigneren, and J. Ruiz Restrepo, “Experimental y no-experimental,” La Sociología en sus Escenarios, no. 18, Aug. 2010. [Online]. Available: https://revistas.udea.edu.co/index.php/ceo/article/view/6545.
C. Manterola and T. Otzen, “Estudios Observacionales: Los Diseños Utilizados con Mayor Frecuencia en Investigación Clínica,” es, International Journal of Morphology, vol. 32, pp. 634–645, Jun. 2014, ISSN: 0717-9502. [Online]. Available: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022014000200042&nrm=iso.
J. Creswell, Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research, ser. Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson, 2012, ISBN: 9780131367395.
C. Fraser, SLAM, SfM and Photogrammetry: What’s in a Name? Interview at the ISPRS Technical Commision II Symposium, 2018. [Online]. Available: https://www.isprs.org/tc2-symposium2018/images/ISPRS-Interview-Fraser.pdf.
K. Hata and S. Savarese, CS231A Course Notes 1: Camera Models, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf.
K. Hata and S. Savarese, CS231A Course Notes 3: Epipolar Geometry, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/03- epipolar-geometry.pdf.
K. Hata and S. Savarese, CS231A Course Notes 4: Stereo Systems and Structure from Motion, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/04-stereo-systems.pdf.
J. Civera, A. J. Davison, and J. M. Martínez Montiel, Structure from motion using the extended kalman filter. Springer, 2012.
Wöhler, Christian, 3D computer vision. Springer, 2013.
D. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004. DOI: 10.1023/b:visi.0000029664.99615.94.
M. A. R. Ahad, Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding, ser. Atlantis Ambient and Pervasive Intelligence. Atlantis Press, 2011, ISBN: 9789491216206.
C. Stachniss, SIFT - 5 Minutes with Cyrill, YouTube, 2020. [Online]. Available: https://www.youtube.com/watch?v=4AvTMVD9ig0.
S. Krig, Computer Vision Metrics: Survey, Taxonomy, and Analysis, ser. SpringerLink : Bücher. Apress, 2014, ISBN: 9781430259305.
D. Tyagi, Introduction to feature detection and matching, Medium, 2019. [Online]. Available: https://medium.com/data-breach/introduction-to-feature-detection-and-matching-65e27179885d.
R. Szeliski, Computer Vision: Algorithms and Applications, ser. Texts in Computer Science. Springer London, 2010, ISBN: 9781848829350.
D. Lowe, “Object recognition from local scale-invariant features,” Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999. DOI: 10.1109/iccv.1999.790410.
R. Brach, “Calculation of crush stiffness coefficients from two-vehicle collisions,” University of Notre Dame, 1997.
J. Neades, “From test collisions to stiffness coefficients,” AiTS, South Cerney, Glos., 2013.
D. E. Siddall and T. D. Day, “Updating the vehicle class categories,” SAE Technical Paper Series,1996. DOI: 10.4271/960897.
D. Vomhof III, Kinetic energy equivalent speed: What is it?, why calculate it?, how to calculate it? 2001. [Online]. Available: http://www.4n6xprt.com/KEES5-4.pdf.
BeamNG GmbH, BeamNG.research, version 1.3.0.0, Oct. 11, 2018. [Online]. Available: https://www.beamng.gmbh/research.
C. Wu, “Towards linear-time incremental structure from motion,” 2013 International Conference on 3D Vision, 2013. DOI: 10.1109/3dv.2013.25.
Y. Furukawa, Clustering Views for Multi-View Stereo, Département d’Informatique de l’ENS, 2010. [Online]. Available: https://www.di.ens.fr/cmvs/.
Y. Furukawa, B. Curless, S. M. Seitz, and R. Szeliski, “Towards internet-scale multi-view stereo,” 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. DOI: 10.1109/cvpr.2010.5539802.
Y. Furukawa and J. Ponce, Patch-based Multi-view Stereo Software, Département d’Informatique de l’ENS, 2010. [Online]. Available: https://www.di.ens.fr/pmvs/.
Y. Furukawa and J. Ponce, “Accurate, dense, and robust multiview stereopsis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 8, pp. 1362–1376, 2010. DOI: 10.1109/tpami.2009.161.
CloudCompare: 3D point cloud and mesh processing software, Open Source Project, 2009. [Online]. Available: https://www.cloudcompare.org/.
Alignment and registration, CloudCompare Wiki, 2015. [Online]. Available: https://www.cloudcompare.org/doc/wiki/index.php?title=Alignment_and_Registration.
ICP, CloudCompare Wiki, 2015. [Online]. Available: https://www.cloudcompare.org/doc/wiki/index.php?title=ICP.
P. Besl and N. McKay, “A method for registration of 3-d shapes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239–256, 1992. DOI: 10.1109/34.121791.
F. Prieto, Visión Tridimensional: Registro o Puesta en Correspondencia. Universidad Nacional de Colombia, 2020.
NHTSA Vehicle Crash Test Database, National Highway Traffic Safety Administration. [Online]. Available: https://www-nrd.nhtsa.dot.gov/database/veh/veh.htm.
D. Margaritis and R. de Vos, Pan-european co-ordinated accident and injury databases, 2002. [Online]. Available: https://ec.europa.eu/transport/road_safety/sites/default/files/pdf/projects_sources/crashtest_database_d4.pdf.
Euro NCAP, YouTube. [Online]. Available: https://www.youtube.com/c/EuroNCAP _forsafercars/videos.
IIHS, YouTube. [Online]. Available: https://www.youtube.com/user/iihs/videos.
Protocole - eléments d’architecture, Tools and Acquisition Protocols for Enchancing Artefacts Documentation. [Online]. Available: http://www.tapenade.gamsau.archi.fr/TAPEnADe/PR_elements_files/PR_elements-fr_1.pdf.
J. Friedt, “Photogrammetric 3d structure reconstruction using micmac,” 2014.
Tom999 and Ghost187, B.I.H.S. Crash Hall, BeamNG, 2018. [Online]. Available: https://www.beamng.com/resources/b-i-h-s-crash-hall.3205/.
J. Morgan and D. Brogan, “How to VisualSFM,” Colorado State University, 2016.
F. Peter, “Generating a Photogrammetric model using VisualSFM, and post-processing with Meshlab,” 2016.
Instruction on reconstruction workflow, Carnegie Mellon University, 2014. [Online]. Available: https://www.cs.cmu.edu/~reconstruction/basic_workflow.html.
G. D. Osterholt, J. R. Cummings, B. Biller, and V. Calhoun, “Updating generic crush stiffness coefficients for accident reconstruction,” SAE Technical Paper 2010-01-1581, 2010. DOI:10.4271/2010-01-1581.
A. C. Sankaranarayanan, A. Veeraraghavan, O. Tuzel, and A. Agrawal, “Specular surface reconstruction from sparse reflection correspondences,” in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 1245–1252. DOI: 10.1109/CVPR.2010.5539826.
S. Konrad, Reconstruction of specular surfaces from reflectance correspondences, Technische Universität Darmstadt, Darmstadt, 2016.
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Prieto Ortiz, Flavio Augustoe5e0629d29d9b754bf18e0f0017122daToquica, Hans171c856836f56b165fe03a7a074bb2c02022-02-22T21:24:51Z2022-02-22T21:24:51Z2021-09https://repositorio.unal.edu.co/handle/unal/81041Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, fotografías, graficasPhotogrammetry is the technique that allows to obtain information from objects in image captures. Structure from Motion is a computer vision technique by which it is possible to obtain a three-dimensional representation of objects visible in a set of image captures. On the other hand, Traffic Accident Reconstruction refers to the set of techniques used for the analysis of traffic accidents. Within this set of techniques, the energy loss models can be found. These models allow to obtain a measure of the severity of a particular traffic accident. In this work, indirect photogrammetry (namely, Structure from Motion) is applied on a set of crash tests images obtained with BeamNG.drive, in order to estimate the energy equivalent speed based on the McHenry energy loss model. The results of this work show that three-dimensional computer vision techniques, such as Structure from Motion, are capable of providing estimations that are comparable to the results provided in other works related to the analysis traffic accidents.La fotogrametría es la técnica que permite obtener información de objectos en capturas de imágenes. Structure from Motion es una técnica de visión de máquina mediante la cual es posible obtener una representación tridimensional de los objetos visibles en un set de captura de imágenes. Por otro lado, la reconstrucción de accidentes de tránsito (Traffic Accident Reconstruction) hace referencia al conjunto de técnicas usadas para el análisis de accidentes de tránsito. En este conjunto de técnicas se pueden encontrar los modelos de pérdida energética. Estos modelos permiten obtener una medida de la severidad de un accidente de tránsito en particular. En este trabajo, la fotogrametría indirecta (específicamente, Structure from Motion) es aplicada en un set de imágenes de pruebas de choque obtenidas con BeamNG.drive, con el fin de estimar la velocidad equivalente a la energía (Energy Equivalent Speed) basada en el modelo de pérdida energética de McHenry. Los resultados de este trabajo muestran que las técnicas de visión tridimensional, tales como Structure from Motion, son capaces de proporcionar estimaciones comparables con otros trabajos relacionados ael análisis de accidentes de tránsito. (Texto tomado de la fuente)MaestríaMagíster en Ingeniería - Ingeniería de Sistemas y ComputaciónSistemas Inteligentes75 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería de Sistemas y ComputaciónDepartamento de Ingeniería de Sistemas e IndustrialFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá000 - Ciencias de la computación, información y obras generales::006 - Métodos especiales de computaciónEnergy loss estimationEnergy equivalent speedTraffic accident reconstructionStructure from motionPhotogrammetryEstimación de pérdida de energíaReconstrucción de accidentes de tránsitoFotogrametríaFotogrametríaReconocimiento topográficoPhotogrammetryTraffic accident energy loss estimation using three-dimensional computer visionEstimación de pérdida de energía en accidentes de tránsito usando visión tridimensionalTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMJ. F. Kerkhoff, “Photographic techniques for accident reconstruction,” SAE Transactions, vol. 94, pp. 292–305, 1985, ISSN: 0096736X. [Online]. Available: http://www.jstor.org/stable/44467584.H. Xu and G. Lu, “Application of photogrammetry to measurement of traffic accident scene,” Traffic and Transportation Studies, 2002.L. Zhang, W. H. Qin, T. J. He, and W. N. Li, “Special considerations for tdoa application to the reconstruction of traffic accidents,” Advanced Materials Research, vol. 255-260, pp. 4090–4094, 2011. DOI: 10.4028/www.scientific.net/amr.255-260.4090.M. Pepe, J. Sobek, and G. Huett, “Three dimensional computerized photogrammetry and its application to accident reconstruction,” International Congress and Exposition Motor Vehicle Accident Reconstruction:, 1989.D. Behring, J. Thesing, H. Becker, and R. Zobel, “Optical coordinate measuring techniques for the determination and visualization of 3d displacements in crash investigations,” Society of Automotive Engineers, 2001.K. Breen and C. Anderson, “The application of photogrammetry to accident reconstruction,” Society of Automotive Engineers, 1986.B. Dierckx, C. De Veuster, and P.-A. Guidault, “Measuring a geometry by photogrammetry: Evaluation of the approach in view of experimental modal analysis on automotive structures,” Proceedings of the 2001 Noise and Vibration Conference, 2020.E. J. Manuel, R. Mink, and D. Kruger, “Videogrammetry in vehicle crash reconstruction with a moving video camera,” SAE Technical Paper Series, 2018. DOI: 10.4271/2018-01-0532.P. Niederer, B. Birchler, F. Mesqui, and Y. Lehareinger, “Computer assisted single-view photogrammetry for accident scene documentation,” SAE International, 1985.M. R. Osman and K. N. Tahar, “3d accident reconstruction using low-cost imaging technique,” Advances in Engineering Software, vol. 100, pp. 231–237, 2016. DOI: 10 . 1016 / j .advengsoft.2016.07.007.L. Pádua, J. Sousa, J. Vanko, J. Hruška, T. Adão, E. Peres, A. Sousa, and J. J. Sousa, “Digital reconstitution of road traffic accidents: A flexible methodology relying on uav surveying and complementary strategies to support multiple scenarios,” International Journal of Environmental Research and Public Health, vol. 17, no. 6, p. 1868, 2020. DOI: 10.3390/ijerph17061868.B. Randles, B. Jones, J. Welcher, T. Szabo, D. Elliott, and C. MacAdams, “The accuracy of photogrammetry vs. hands-on measurement techniques used in accident reconstruction,” SAE International, 2010.T. Terpstra, T. Voitel, and A. Hashemian, “A survey of multi-view photogrammetry software for documenting vehicle crush,” SAE Technical Paper Series, 2016. DOI: 10.4271/2016- 01-1475.X. Du, X. Jin, X. Zhang, J. Shen, and X. Hou, “Geometry features measurement of traffic accident for reconstruction based on close-range photogrammetry,” Advances in Engineering Software, vol. 40, no. 7, pp. 497–505, 2009. DOI: 10.1016/j.advengsoft.2008.09.002.I. Han and H. Kang, “Three-dimensional crush scanning methods for reconstruction of vehicle collision accidents,” International Journal of Automotive Technology, vol. 17, no. 1, pp. 91–98, 2016. DOI: 10.1007/s12239-016-0008-y.K. L. Campbell, “Energy basis for collision severity,” SAE Transactions, vol. 83, pp. 2114–2126, 1974, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44657484.United States. National Highway Traffic Safety Administration. Accident Investigation Division, CRASH3 User’s Guide and Technical Manual. The Division, 1981. [Online]. Available: https://books.google.com.co/books?id=tv85AQAAMAAJ.R. A. Smith and J. T. Noga, “Accuracy and sensitivity of crash,” SAE Technical Paper Series, 1982. DOI: 10.4271/821169.R. L. Woolley, C. Y. Warner, and M. D. Tagg, “Inaccuracies in the crash3 program,” SAE Transactions, vol. 94, pp. 380–398, 1985, ISSN: 0096736X. [Online]. Available: http://www.jstor.org/stable/44467589.B. McHenry, “The algorithm of CRASH,” United States: McHenry Software, Inc., 2001.A. G. Fonda, “Principles of crush energy determination,” SAE Transactions, vol. 108, pp. 392–406, 1999, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44667911.D. Vangi, “Energy loss in vehicle to vehicle oblique impact,” International Journal of Impact Engineering, vol. 36, no. 3, pp. 512–521, 2009. DOI: 10.1016/j.ijimpeng.2008.09.001.M. Gidlewski, L. Prochowski, L. Jemioł, and D. Żardecki, “The process of front-to-side collision of motor vehicles in terms of energy balance,” Nonlinear Dynamics, vol. 97, no. 3, pp. 1877–1893, 2018. DOI: 10.1007/s11071-018-4688-x.G. A. Nystrom, G. Kost, and S. M. Werner, “Stiffness parameters for vehicle collision analysis,” SAE Transactions, vol. 100, pp. 169–176, 1991, ISSN: 0096736X, 25771531. [Online]. Available: http://www.jstor.org/stable/44632021.J. A. Neptune, G. Y. Blair, and J. E. Flynn, “A method for quantifying vehicle crush stiffness coefficients,” SAE Technical Paper Series, 1992. DOI: 10.4271/920607.A. R. Várkonyi-kóczy, A. Rövid, and P. Várlaki, “Intelligent methods for car deformation modeling and crash speed estimation,” 2004.I. Han and H. Kang, “Determination of the collision speed of a vehicle from evaluation of the crush volume using photographs,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol. 230, no. 4, pp. 479–490, 2015. DOI: 10.1177/0954407015586906.J. Goicolea, “Estructuras sometidas a impacto,” 2000.R. Burdzik, P. Folega, L. Konieczny, B. Lazarz, Z. Stanik, and J. Warczek, “Analysis of material deformation work measures in determination of a vehicle’s collision speed,” Archives of Materials Science and Engineering, 2020.F. Berg, F. Walz, M. Muser, H. Bürkle, and J. Epple, “Implications of Velocity Change Delta-V and Energy Equivalent Speed EES for Injury Mechanism Assesment in Various Colission Configurations,” IRCOBI Conference - Göteborg, 1998.G. Păduraru, “Vehicle speed correlation with deformation amplitude due to adult pedestrian impact in car traffic accidents,” Ovidius University Annals of Mechanical, Industrial and Maritime Engineering, 2008.A. Toglia, G. Stephens, D. Michalski, and J. Rodriguez, “Applications of photomodeler in accident reconstruction,” 2005 ASME International Mechanical Engineering Congress and Exposition, 2005.C. Fraser, “Accident reconstruction via digital close-range photogrammetry,” 2006.A. Morales, D. Gonzalez-Aguilera, M. Gutiérrez, and A. López, “Energy analysis of road accidents based on close-range photogrammetry,” Remote Sensing, vol. 7, no. 11, pp. 15 161–15 178, 2015. DOI: 10.3390/rs71115161.D. A. Jurkofsky, “Accuracy of suas photogrammetry for use in accident scene diagramming,” SAE International Journal of Transportation Safety, vol. 3, no. 2, pp. 136–152, 2015. DOI: 10 .4271/2015-01-1426.Z. Bo, X. Haitao, L. Lulu, J. Jun, Z. Jianyue, and T. Yiping, “Development of coordinate-machine of the scene of road traffic accident based on binocular stereo omni-directional vision sensors,” Procedia Engineering, vol. 24, pp. 262–266, 2011. DOI: 10.1016/j.proeng.2011.11.2638.F. Mesqui, P. Niederer, M. Schlumpf, Y. Lehareinger, and J. Walton, “Semi-automatic reconstruction of the spatial trajectory of an impacted pedestrian surrogate using high-speed cinephotogrammetry and digital image analysis,” Journal of Biomechanical Engineering, vol. 106, no. 4, pp. 357–359, 1984. DOI: 10.1115/1.3138505.V. Žuraulis, L. Levulytė, and E. Sokolovskij, “Vehicle speed prediction from yaw marks using photogrammetry of image of traffic accident scene,” Procedia Engineering, vol. 134, pp. 89–94, 2016. DOI: 10.1016/j.proeng.2016.01.043.B. Epstein and B. G. Westlake, “Determination of vehicle speed from recorded video using reverse projection photogrammetry and file metadata,” Journal of Forensic Sciences, vol. 64, no. 5, pp. 1523–1529, 2019. DOI: 10.1111/1556-4029.14053.D. F. Tandy, C. Coleman, J. Colborn, T. Hoover, and J. Bae, “Benefits and methodology for dimensioning a vehicle using a 3d scanner for accident reconstruction purposes,” SAE Technical Paper Series, 2012. DOI: 10.4271/2012-01-0617.J. Arnold, H. Bösch, and M. Braun, “Reconstruction of a multi vehicle collision on a highway: Combining forensic evidence examination, 3d-scanning and 3d-photogrammetry with numerical accident reconstruction methods,” IRCOBI Conference - Bern (Switzerland), 2008.L. Barazzetti, R. Sala, M. Scaioni, C. Cattaneo, D. Gibelli, A. Giussani, P. Poppa, F. Roncoroni, and A. Vandone, “3d scanning and imaging for quick documentation of crime and accident scenes,” Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XI, 2012. DOI: 10.1117/12.920728.U. Buck, K. Buße, L. Campana, F. Gummel, C. Schyma, and C. Jackowski, “What happened before the run over? morphometric 3d reconstruction,” Forensic Science International, vol. 306, p. 110 059, 2020. DOI: 10.1016/j.forsciint.2019.110059.U. Buck, S. Naether, M. Braun, S. Bolliger, H. Friederich, C. Jackowski, E. Aghayev, A. Christe, P. Vock, and R. Dirnhofer, “Application of 3d documentation and geometric reconstruction methods in traffic accident analysis: With high resolution surface scanning, radiological msct/mri scanning and real data based animation,” Forensic Science International, vol. 170, no. 1, pp. 20–28, 2007. DOI: 10.1016/j.forsciint.2006.08.024.W. Baier, M. J. Donnelly, M. Payne, and M. A. Williams, “A holistic multi-scale approach to using 3d scanning technology in accident reconstruction,” Journal of Forensic Sciences, vol. 65, no. 5, pp. 1774–1778, 2020. DOI: 10.1111/1556-4029.14405.U. Buck, S. Naether, B. Räss, C. Jackowski, and M. J. Thali, “Accident or homicide - virtual crime scene reconstruction using 3d methods,” Forensic Science International, vol. 225, no. 1-3, pp. 75–84, 2013. DOI: 10.1016/j.forsciint.2012.05.015.C. Strother, R. Kent, and C. Warner, “Estimating vehicle deformation energy for vehicles struck in the side,” Advances in Safety Technology, 1998.N. Carter, A. Hashemian, N. Rose, and W. Neale, “Evaluation of the accuracy of image based scanning as a basis for photogrammetric reconstruction of physical evidence,” SAE International, 2020.William Kevin Peach v. Lynsey E. McGovern. Supreme Court of the State of Illinois No:123156, 2018.R. Fay, “Analytical applications of 3-d imaging in vehicle accident studies,” Accident Reconstruction: Technology and Animation VI, 1996.D. Rudny and D. Sallmann, “The use of electronic survey equipment in the creation of accident scene diagrams,” Accident Reconstruction: Technology and Animation V, 1995.H. Toquica, “Estado de arte: Visión de máquina y técnicas de inteligencia artificial para la deteccion de infracciones de tránsito por alta velocidad,” Humanities Commons, 2020. DOI:10.17613/81qy-1r28.Siniestros en las vías, un problema de salud pública, El Tiempo, Feb. 2018. [Online]. Available: https://www.eltiempo.com/salud/informe-de-la-oms-sobre-accidentes-de-transito-en-el-mundo-302888 (visited on 05/01/2020).N. Tumbas, R. Kinney, and G. Smith, “Photogrammetry and accident reconstruction: Experimental results,” Accident Reconstruction: Technology and Animation IV, 1994.R. Hernández Sampieri, C. Fernández Collado, and M. d. P. Baptista Lucio, Metodología de la investigación (5a. ed.) McGraw-Hill Interamericana, 2000.G. Agudelo, M. Aigneren, and J. Ruiz Restrepo, “Experimental y no-experimental,” La Sociología en sus Escenarios, no. 18, Aug. 2010. [Online]. Available: https://revistas.udea.edu.co/index.php/ceo/article/view/6545.C. Manterola and T. Otzen, “Estudios Observacionales: Los Diseños Utilizados con Mayor Frecuencia en Investigación Clínica,” es, International Journal of Morphology, vol. 32, pp. 634–645, Jun. 2014, ISSN: 0717-9502. [Online]. Available: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022014000200042&nrm=iso.J. Creswell, Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research, ser. Educational Research: Planning, Conducting, and Evaluating Quantitative and Qualitative Research. Pearson, 2012, ISBN: 9780131367395.C. Fraser, SLAM, SfM and Photogrammetry: What’s in a Name? Interview at the ISPRS Technical Commision II Symposium, 2018. [Online]. Available: https://www.isprs.org/tc2-symposium2018/images/ISPRS-Interview-Fraser.pdf.K. Hata and S. Savarese, CS231A Course Notes 1: Camera Models, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/01-camera-models.pdf.K. Hata and S. Savarese, CS231A Course Notes 3: Epipolar Geometry, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/03- epipolar-geometry.pdf.K. Hata and S. Savarese, CS231A Course Notes 4: Stereo Systems and Structure from Motion, Standford University, 2017. [Online]. Available: https://web.stanford.edu/class/cs231a/course_notes/04-stereo-systems.pdf.J. Civera, A. J. Davison, and J. M. Martínez Montiel, Structure from motion using the extended kalman filter. Springer, 2012.Wöhler, Christian, 3D computer vision. Springer, 2013.D. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004. DOI: 10.1023/b:visi.0000029664.99615.94.M. A. R. Ahad, Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding, ser. Atlantis Ambient and Pervasive Intelligence. Atlantis Press, 2011, ISBN: 9789491216206.C. Stachniss, SIFT - 5 Minutes with Cyrill, YouTube, 2020. [Online]. Available: https://www.youtube.com/watch?v=4AvTMVD9ig0.S. Krig, Computer Vision Metrics: Survey, Taxonomy, and Analysis, ser. SpringerLink : Bücher. Apress, 2014, ISBN: 9781430259305.D. Tyagi, Introduction to feature detection and matching, Medium, 2019. [Online]. Available: https://medium.com/data-breach/introduction-to-feature-detection-and-matching-65e27179885d.R. Szeliski, Computer Vision: Algorithms and Applications, ser. Texts in Computer Science. Springer London, 2010, ISBN: 9781848829350.D. Lowe, “Object recognition from local scale-invariant features,” Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999. DOI: 10.1109/iccv.1999.790410.R. Brach, “Calculation of crush stiffness coefficients from two-vehicle collisions,” University of Notre Dame, 1997.J. Neades, “From test collisions to stiffness coefficients,” AiTS, South Cerney, Glos., 2013.D. E. Siddall and T. D. Day, “Updating the vehicle class categories,” SAE Technical Paper Series,1996. DOI: 10.4271/960897.D. Vomhof III, Kinetic energy equivalent speed: What is it?, why calculate it?, how to calculate it? 2001. [Online]. Available: http://www.4n6xprt.com/KEES5-4.pdf.BeamNG GmbH, BeamNG.research, version 1.3.0.0, Oct. 11, 2018. [Online]. Available: https://www.beamng.gmbh/research.C. Wu, “Towards linear-time incremental structure from motion,” 2013 International Conference on 3D Vision, 2013. DOI: 10.1109/3dv.2013.25.Y. Furukawa, Clustering Views for Multi-View Stereo, Département d’Informatique de l’ENS, 2010. [Online]. Available: https://www.di.ens.fr/cmvs/.Y. Furukawa, B. Curless, S. M. Seitz, and R. Szeliski, “Towards internet-scale multi-view stereo,” 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. DOI: 10.1109/cvpr.2010.5539802.Y. Furukawa and J. Ponce, Patch-based Multi-view Stereo Software, Département d’Informatique de l’ENS, 2010. [Online]. Available: https://www.di.ens.fr/pmvs/.Y. Furukawa and J. Ponce, “Accurate, dense, and robust multiview stereopsis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 8, pp. 1362–1376, 2010. DOI: 10.1109/tpami.2009.161.CloudCompare: 3D point cloud and mesh processing software, Open Source Project, 2009. [Online]. Available: https://www.cloudcompare.org/.Alignment and registration, CloudCompare Wiki, 2015. [Online]. Available: https://www.cloudcompare.org/doc/wiki/index.php?title=Alignment_and_Registration.ICP, CloudCompare Wiki, 2015. [Online]. Available: https://www.cloudcompare.org/doc/wiki/index.php?title=ICP.P. Besl and N. McKay, “A method for registration of 3-d shapes,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239–256, 1992. DOI: 10.1109/34.121791.F. Prieto, Visión Tridimensional: Registro o Puesta en Correspondencia. Universidad Nacional de Colombia, 2020.NHTSA Vehicle Crash Test Database, National Highway Traffic Safety Administration. [Online]. Available: https://www-nrd.nhtsa.dot.gov/database/veh/veh.htm.D. Margaritis and R. de Vos, Pan-european co-ordinated accident and injury databases, 2002. [Online]. Available: https://ec.europa.eu/transport/road_safety/sites/default/files/pdf/projects_sources/crashtest_database_d4.pdf.Euro NCAP, YouTube. [Online]. Available: https://www.youtube.com/c/EuroNCAP _forsafercars/videos.IIHS, YouTube. [Online]. Available: https://www.youtube.com/user/iihs/videos.Protocole - eléments d’architecture, Tools and Acquisition Protocols for Enchancing Artefacts Documentation. [Online]. Available: http://www.tapenade.gamsau.archi.fr/TAPEnADe/PR_elements_files/PR_elements-fr_1.pdf.J. Friedt, “Photogrammetric 3d structure reconstruction using micmac,” 2014.Tom999 and Ghost187, B.I.H.S. Crash Hall, BeamNG, 2018. [Online]. Available: https://www.beamng.com/resources/b-i-h-s-crash-hall.3205/.J. Morgan and D. Brogan, “How to VisualSFM,” Colorado State University, 2016.F. Peter, “Generating a Photogrammetric model using VisualSFM, and post-processing with Meshlab,” 2016.Instruction on reconstruction workflow, Carnegie Mellon University, 2014. [Online]. Available: https://www.cs.cmu.edu/~reconstruction/basic_workflow.html.G. D. Osterholt, J. R. Cummings, B. Biller, and V. Calhoun, “Updating generic crush stiffness coefficients for accident reconstruction,” SAE Technical Paper 2010-01-1581, 2010. DOI:10.4271/2010-01-1581.A. C. Sankaranarayanan, A. Veeraraghavan, O. Tuzel, and A. Agrawal, “Specular surface reconstruction from sparse reflection correspondences,” in 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, pp. 1245–1252. DOI: 10.1109/CVPR.2010.5539826.S. Konrad, Reconstruction of specular surfaces from reflectance correspondences, Technische Universität Darmstadt, Darmstadt, 2016.BibliotecariosEstudiantesInvestigadoresMaestrosPúblico generalORIGINAL1033757650.2021.pdf1033757650.2021.pdfTesis de Maestría en Ciencias de la Computaciónapplication/pdf21621877https://repositorio.unal.edu.co/bitstream/unal/81041/1/1033757650.2021.pdfd63a463ee58449cbcef7d6d54c387c75MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81041/2/license.txt8153f7789df02f0a4c9e079953658ab2MD52THUMBNAIL1033757650.2021.pdf.jpg1033757650.2021.pdf.jpgGenerated Thumbnailimage/jpeg5449https://repositorio.unal.edu.co/bitstream/unal/81041/3/1033757650.2021.pdf.jpg8d65b99eeb861b0dd730d65b8b5ddd34MD53unal/81041oai:repositorio.unal.edu.co:unal/810412023-08-01 23:04:13.658Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

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