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PAMI
2002

Object Tracking with Bayesian Estimation of Dynamic Layer Representations

9 years 9 months ago
Object Tracking with Bayesian Estimation of Dynamic Layer Representations
Decomposing video frames into coherent two-dimensional motion layers is a powerful method for representing videos. Such a representation provides an intermediate description that enables applications such as object tracking, video summarization and visualization, video insertion, and sprite-based video compression. Previous work on motion layer analysis has largely concentrated on two-frame or multiframe batch formulations. The temporal coherency of motion layers and the domain constraints on shapes have not been exploited. This paper introduces a complete dynamic motion layer representation in which spatial and temporal constraints on shape, motion, and layer appearance are modeled and estimated in a maximum a posteriori (MAP) framework using the generalized expectation-maximization (EM) algorithm. In order to limit the computational complexity of tracking arbitrarily shaped layer ownership, we propose a shape prior that parameterizes the representation of shape and prevents motion la...
Hai Tao, Harpreet S. Sawhney, Rakesh Kumar
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where PAMI
Authors Hai Tao, Harpreet S. Sawhney, Rakesh Kumar
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