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Comparative Evaluation of Stationary Foreground Object Detection Algorithms Based on Background Subtraction Techniques
- Source :
- AVSS, Biblos-e Archivo. Repositorio Institucional de la UAM, instname
- Publication Year :
- 2009
- Publisher :
- IEEE, 2009.
-
Abstract
- Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Á. Bayona, J. C. SanMiguel, and J. M. Martínez, "Comparative evaluation of stationary foreground object detection algorithms based on background subtraction techniques" in Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance. AVSS 2009, p. 25 - 30<br />In several video surveillance applications, such as the detection of abandoned/stolen objects or parked vehicles,the detection of stationary foreground objects is a critical task. In the literature, many algorithms have been proposed that deal with the detection of stationary foreground objects, the majority of them based on background subtraction techniques. In this paper we discuss various stationary object detection approaches comparing them in typical surveillance scenarios (extracted from standard datasets). Firstly, the existing approaches based on background-subtraction are organized into categories. Then, a representative technique of each category is selected and described. Finally, a comparative evaluation using objective and subjective criteria is performed on video surveillance sequences selected from the PETS 2006 and i-LIDS for AVSS 2007 datasets, analyzing the advantages and drawbacks of each selected approach.<br />This work has partially supported by the Cátedra UAMInfoglobal ("Nuevas tecnologías de vídeo aplicadas a sistemas de video-seguridad"), the Spanish Administration agency CDTI (CENIT-VISION 2007-1007), by the Spanish Government (TEC2007-65400 SemanticVideo), by the Comunidad de Madrid (S-050/TIC-0223- ProMultiDis), by the Consejería de Educación of the Comunidad de Madrid, and by The European Social Fund.
- Subjects :
- Informática
Telecomunicaciones
Background subtraction
Pixel
Layout
Computer science
business.industry
Intelligent vehicles
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Cameras
Object detection
Comparative evaluation
Task (computing)
Stationary object
Computer vision
Noise (video)
Artificial intelligence
business
Algorithm
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
- Accession number :
- edsair.doi.dedup.....84499bb9558b568095d7e94a9bce16a7
- Full Text :
- https://doi.org/10.1109/avss.2009.35