People detection based on appearance and motion models
Entidad
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesEditor
Institute of Electrical and Electronics EngineersFecha de edición
2011Cita
10.1109/AVSS.2011.6027333
8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2011, IEEE, 2011. 256-260
ISBN
978-1-4577-0843-5 (online); 978-1-4577-0844-2 (print)DOI
10.1109/AVSS.2011.6027333Financiado por
This work has been partially supported by the Cátedra UAM-Infoglobal ("Nuevas tecnologías de vídeo aplicadas a sistemas de video-seguridad") and by the Universidad Autónoma de Madrid (“FPI-UAM: Programa propio de ayudas para la Formación de Personal Investigador”)Versión del editor
http://dx.doi.org/10.1109/AVSS.2011.6027333Materias
Implicit motion model; Implicit shape model; MoSIFT; People detection; TelecomunicacionesNota
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. A. Garcia-Martin, A. Hauptmann, and J. M. Martínez "People detection based on appearance and motion models", in 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2011, p. 256-260Derechos
© 2011 IEEEResumen
The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our new people motion detector produces results comparable to the state of the art and that the proposed multimodal fusion system improves the obtained results combining the three information sources.
Lista de ficheros
Google Scholar:García-Martín, Álvaro
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Hauptmann, Alex
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Martínez Sánchez, José María
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