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A Fast Object Tracking Approach Based on the Motion Vector in a Compressed Domain : Un approccio per il tracking veloce basato sul vettore del moto in un dominio compresso, in: International Journal of Advanced Robotic Systems

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Autor Wang, Hui-bin; Shen, Jie; Chen, Zhe; Shen, Jun-lei
Publicat  InTech Open Access Publisher, 2013
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Abstract Particle set sampling and weighting are both at
the core of particle filter‐based object tracking methods.
Aiming to optimally represent the objectʹs motion state, a
large amount of particles ‐ in the classical particle method ‐
is a prerequisite. The high‐cost calculation of these particles
significantly slows down the convergence of the algorithm.
To this problem, a prior approach which originated from
the process of video compressing and uncompressing is
introduced to optimize the phase of particle sampling,
making the collected particles centre on and cover the
object region in the current image. This advantage
dramatically reduces the number of particles required by
the regularized particle sampling method, solving the
problem of the high computational cost for tracking
objects, while the performance of the algorithm is stable.
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no fulltext found International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Publicat: 2004
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Documents: International Journal of Advanced Robotic Systems
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Time of publication 2013
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License

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