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PCM
2004
Springer
168views Multimedia» more  PCM 2004»
14 years 22 days ago
Approximating Inference on Complex Motion Models Using Multi-model Particle Filter
Abstract. Due to its great ability of conquering clutters, which is especially useful for high-dimensional tracking problems, particle filter becomes popular in the visual trackin...
Jianyu Wang, Debin Zhao, Shiguang Shan, Wen Gao
CVIU
2006
317views more  CVIU 2006»
13 years 7 months ago
A general method for human activity recognition in video
In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...
Neil Robertson, Ian D. Reid
ICARCV
2006
IEEE
420views Robotics» more  ICARCV 2006»
14 years 1 months ago
Recognizing People's Faces: from Human to Machine Vision
— As confirmed by recent neurophysiological studies, the use of dynamic information is extremely important for humans in visual perception of biological forms and motion. Apart ...
Massimo Tistarelli, Manuele Bicego, Enrico Grosso
ICCV
1995
IEEE
13 years 11 months ago
Facial Expression Recognition Using a Dynamic Model and Motion Energy
Previous efforts at facial expression recognition have been based on the Facial Action Coding System (FACS), a representation developed in order to allow human psychologists to co...
Irfan A. Essa, Alex Pentland
CVPR
2009
IEEE
13 years 11 months ago
Switching Gaussian Process Dynamic Models for simultaneous composite motion tracking and recognition
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...
Jixu Chen, Minyoung Kim, Yu Wang, Qiang Ji