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» A probabilistic framework for object recognition in video
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ICIP
2009
IEEE
14 years 8 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...
WACV
2012
IEEE
12 years 3 months ago
Simultaneous inference of activity, pose and object
Human movements are important cues for recognizing human actions, which can be captured by explicit modeling and tracking of actor or through space-time low-level features. Howeve...
Furqan M. Khan, Vivek Kumar Singh, Ram Nevatia
IBPRIA
2005
Springer
14 years 1 months ago
A 3D Dynamic Model of Human Actions for Probabilistic Image Tracking
Abstract. In this paper we present a method suitable to be used for human tracking as a temporal prior in a particle filtering framework such as CONDENSATION [5]. This method is f...
Ignasi Rius, Daniel Rowe, Jordi Gonzàlez, F...
ICCV
2003
IEEE
14 years 9 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
ICIP
2005
IEEE
14 years 9 months ago
Off-line multiple object tracking using candidate selection and the Viterbi algorithm
This paper presents a probabilistic framework for off-line multiple object tracking. At each timestep, a small set of deterministic candidates is generated which is guaranteed to ...
Anil C. Kokaram, François Pitié, Roz...