- -

Ground truth annotation of traffic video data

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Ground truth annotation of traffic video data

Mostrar el registro completo del ítem

Mossi García, JM.; Albiol Colomer, AJ.; Albiol Colomer, A.; Oliver Moll, J. (2014). Ground truth annotation of traffic video data. Multimedia Tools and Applications. 1-14. https://doi.org/10.1007/s11042-013-1396-x

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/56854

Ficheros en el ítem

Metadatos del ítem

Título: Ground truth annotation of traffic video data
Autor: Mossi García, José Manuel Albiol Colomer, Antonio José Albiol Colomer, Alberto Oliver Moll, Javier
Entidad UPV: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Fecha difusión:
Resumen:
This paper presents a software application to generate ground-truth data on video files from traffic surveillance cameras used for Intelligent Transportation Systems (IT systems). The computer vision system to be evaluated ...[+]
Palabras clave: Traffic , Ground truth , Vehicle , Video , Intelligent transportation systems
Derechos de uso: Reserva de todos los derechos
Fuente:
Multimedia Tools and Applications. (issn: 1380-7501 ) (eissn: 1573-7721 )
DOI: 10.1007/s11042-013-1396-x
Editorial:
Springer Verlag (Germany)
Versión del editor: http://dx.doi.org/10.1007/s11042-013-1396-x
Código del Proyecto:
info:eu-repo/grantAgreement/MICINN//TEC2009-09146/ES/Nuevas Tecnicas Para Video Vigilancia Inteligente/
Agradecimientos:
This work was funded by the Spanish Government project MARTA under the CENIT program and CICYT contract TEC2009-09146.
Tipo: Artículo

References

Albiol A et al (2011) Detection of parked vehicles using spatiotemporal maps. IEEE Trans Intell Transport Syst 12(4):1277–1291

Blunsden SJ, Fisher R (2010) The BEHAVE video dataset: ground truthed video for multi-person behavior classification. Annal British Mach Vis Assoc 4:1–12

Bradski G, Kaehler A (2008) Learning OpenCV: Computer vision with the OpenCV library. O'Reilly Media, Incorporated [+]
Albiol A et al (2011) Detection of parked vehicles using spatiotemporal maps. IEEE Trans Intell Transport Syst 12(4):1277–1291

Blunsden SJ, Fisher R (2010) The BEHAVE video dataset: ground truthed video for multi-person behavior classification. Annal British Mach Vis Assoc 4:1–12

Bradski G, Kaehler A (2008) Learning OpenCV: Computer vision with the OpenCV library. O'Reilly Media, Incorporated

Brooke J. SUS: a “quick and dirty” usability scale. Usability evaluation in industry. Taylor and Francis

Brostow GJ et al (2009) Semantic object classes in video: a high-definition ground truth database. Pattern Recognit Lett 30(2):88–97

Buch N et al (2011) A review of computer vision techniques for the analysis of urban traffic. IEEE Trans Intell Transp Syst 12(3):920–939

D’Orazio T et al. (2009) A semi-automatic system for ground truth generation of soccer video sequences. Advanced Video and Signal Based Surveillance, 2009. AVSS’09. Sixth IEEE International Conference on (Sep. 2009), 559–564

Dollar P et al (2012) Pedestrian detection: an evaluation of the state of the art. IEEE Trans Pattern Anal Mach Intell 34(4):743–761

Faro A et al (2011) Adaptive background modeling integrated with luminosity sensors and occlusion processing for reliable vehicle detection. IEEE Trans Intell Transport Syst 12(4):1398–1412

Giro-i-Nieto X et al (2010) GAT: a graphical annotation tool for semantic regions. Multimed Tool Appl 46(2–3):155–174

i-LIDS. Image Library for Intelligent Detection Systems: www.ilids.co.uk . Home Office Scientific Development Branch, United Kingdom. Last Accessed February 2013

Kasturi R et al (2009) Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol. IEEE Trans Pattern Anal Mach Intell 31(2):319–336

Laganière R (2011) OpenCV 2 computer vision application programming cookbook. Packt Pub Limited

Lorist MM et al (2000) Mental fatigue and task control: planning and preparation. Psychophysiology 37(5):614–625

Russell B et al (2008) LabelMe: a database and web-based tool for image annotation. Int J Comput Vis 77(1):157–173

Serrano M, Gracía J, Patricio M, Molina J (2010). Interactive video annotation tool. Distributed Computing and Artificial Intelligence, 325–332

Traffic City Cameras. Ajuntament de València, Spain. http://camaras.valencia.es . Last Accessed February 2013

TREC video retrieval evaluation. http://www-nlpir.nist.gov/projects/trecvid/

Vezzani R, Cucchiara R (2010) Video Surveillance Online Repository (ViSOR): an integrated framework. Multimed Tool Appl 50(2):359–380

ViPER: the video performance evaluation resource: http://viper-toolkit.sourceforge.net/

Volkmer T et al. (2005) A web-based system for collaborative annotation of large image and video collections: an evaluation and user study. Proceedings of the 13th annual ACM international conference on Multimedia (New York, NY, USA, 2005), 892–901

Zhang HB, Li SA, Chen SY, Su SZ, Duh DJ, Li SZ (2012) Adaptive photograph retrieval method. Multimedia Tools and Applications, Published online September 2012.

Zou Y et al (2011) Traffic incident classification at intersections based on image sequences by HMM/SVM classifiers. Multimed Tool Appl 52(1):133–145

[-]

recommendations

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro completo del ítem