Regression based pose estimation with automatic occlusion detection and rectification
Human pose estimation is a classic problem in computer vision. Statistical models based on part-based modelling and the pictorial structure framework have been widely used recently for articulated human pose estimation. However, the performance of these models has been limited due to the presence of self-occlusion. This paper presents a learning-based framework to automatically detect and recover self-occluded body parts. We learn two different models: one for detecting occluded parts in the...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings - IEEE International Conference on Multimedia and Expo|
|01_Radwan_Regression_based_pose_2012.pdf||722.6 kB||Adobe PDF||Request a copy|
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