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PCM
2004
Springer
168views Multimedia» more  PCM 2004»
13 years 10 months 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
NIPS
2000
13 years 6 months ago
Keeping Flexible Active Contours on Track using Metropolis Updates
Condensation, a form of likelihood-weighted particle filtering, has been successfully used to infer the shapes of highly constrained "active" contours in video sequences...
Trausti T. Kristjansson, Brendan J. Frey
ISPAN
2009
IEEE
13 years 12 months ago
High Speed Articulated Object Tracking Using GPUs: A Particle Filter Approach
—This paper presents a novel application of the GPU processing power to a very computationally demanding articulated human body tracking problem in a view-based approach. This wo...
Raúl Cabido, David Concha, Juan José...
EVENT
2001
140views more  EVENT 2001»
13 years 6 months ago
Multimodal 3-D Tracking and Event Detection via the Particle Filter
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...
CVPR
2003
IEEE
14 years 7 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...