Constraint integration for efficient multiview pose estimation with self-occlusions

IEEE Transactions on Pattern Analysis and Machine Intelligence
Abhinav GuptaLarry S Davis

Abstract

Automatic initialization and tracking of human pose is an important task in visual surveillance. We present a part-based approach that incorporates a variety of constraints in a unified framework. These constraints include the kinematic constraints between parts that are physically connected to each other, the occlusion of one part by another and the high correlation between the appearance of certain parts, such as the arms. The location probability distribution of each part is determined by evaluating appropriate likelihood measures. The graphical (non-tree) structure representing the interdependencies between parts is utilized to "connect" such part distributions via nonparametric belief propagation. Methods are also developed to perform this optimization efficiently in the large space of pose configurations.

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Citations

Mar 23, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Vlad I MorariuLarry S Davis
Aug 22, 2009·IEEE Transactions on Pattern Analysis and Machine Intelligence·Abhinav GuptaLarry S Davis
Feb 1, 2012·IEEE Transactions on Visualization and Computer Graphics·Joong-Ho WonSandy Napel
Aug 19, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Ananth RanganathanJeffrey Ho

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