Shadow detection in video surveillance by maximizing agreement between independent detectors
EntityUAM. Departamento de Ingeniería Informática
PublisherInstitute of Electrical and Electronics Engineers
10.1109/ICIP.2009.541353216th IEEE International Conference on Image Processing, ICIP 2009, IEEE, 2009. 1141-1144
ISBN978-1-4244-5655-0 (online); 978-1-4244-5653-6 (print)
Funded byWork supported by the Spanish Government (TEC2007- 65400 SemanticVideo), by Cátedra Infoglobal-UAM for “Nuevas Tecnologías de video aplicadas a la seguridad”, by the Spanish Administration agency CDTI (CENIT-VISION 2007-1007), 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.
ProjectComunidad de Madrid. S2006/TIC-0233/PROMULTIDIS
SubjectsDetectors agreement; Mutual information; Shadow detection; Video processing; Video surveillance; Informática; Telecomunicaciones
NotePersonal 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. J. C. SanMiguel, and J. M. Martínez, "Shadow detection in video surveillance by maximizing agreement between independent detectors", in 16th IEEE International Conference on Image Processing, ICIP 2009. p. 1141-1144
Rights© 2009 IEEE
This paper starts from the idea of automatically choosing the appropriate thresholds for a shadow detection algorithm. It is based on the maximization of the agreement between two independent shadow detectors without training data. Firstly, this shadow detection algorithm is described and then, it is adapted to analyze video surveillance sequences. Some modifications are introduced to increase its robustness in generic surveillance scenarios and to reduce its overall computational cost (critical in some video surveillance applications). Experimental results show that the proposed modifications increase the detection reliability as compared to some previous shadow detection algorithms and performs considerably well across a variety of multiple surveillance scenarios.
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