Per citar aquest document:
Prior Knowledge Based Motion Model Representation
Sappa, Angel Domingo (Centre de Visió per Computador (Bellaterra, Catalunya))
Aifanti, Niki (Informatics & Telematics Institute (Grècia))
Malassiotis, Sotiris (Informatics & Telematics Institute (Grècia))
Strintzis, Michael G. (Informatics & Telematics Institute (Grècia))

Data: 2005
Resum: This paper presents a new approach for human walking modeling from monocular image sequences. A kinematics model and a walking motion model are introduced in order to exploit prior knowledge. The proposed technique consists of two steps. Initially, an efficient feature point selection and tracking approach is used to compute feature points’ trajectories. Peaks and valleys of these trajectories are used to detect key frames—frames where both legs are in contact with the floor. Secondly, motion models associated with each joint are locally tuned by using those key frames. Differently than previous approaches, this tuning process is not performed at every frame, reducing CPU time. In addition, the movement’s frequency is defined by the elapsed time between two consecutive key frames, which allows handling walking displacement at different speed. Experimental results with different video sequences are presented.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Model based representations ; Human walking modeling ; Human motion tracking ; Model basat en representacions ; Model de caminada humana ; Moviment humà ; Modelo basado en representaciones ; Modelo de caminar humano ; Movimiento humano
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 5 n. 3 (2005) p. 55-67, ISSN 1577-5097

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