Pictorial Structures Revisited: People Detection and Articulated Pose Estimation

Non-rigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and often address different special cases, such as pedestrian detection or upper body pose estimation in TV footage. This paper shows that such specialization may not be necessary, and proposes a generic approach based on the pictorial structures framework. We show that the right selection of components for both appearance and spatial modeling is crucial for general applicability and overall performance of the model. The appearance of body parts is modeled using densely sampled shape context descriptors and discriminatively trained AdaBoost classifiers. Furthermore, we interpret the normalized margin of each classifier as likelihood in a generative model. Non-Gaussian relationships between parts are represented as Gaussians in the coordinate system of the joint between parts. The marginal posterior of ...

• Type: Conference
• Year: 2009
• Where: CVPR
• Authors: Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU Darmstadt), Bernt Schiele (TU Darmstadt)
• Keywords: AdaBoost Classifiers, Articulated Pose Estimation, Computer Vision, CVPR 2009, Non-rigid Object Detection, Object Detection, Object Recognition, Shape Context Descriptors