A b s t r a c t

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Pose estimation involves reconstructing the configuration of a moving body from images sequences. In this paper we present a general framework for pose estimation of unknown objects based on Shafer’s evidential reasoning. During learning an evidential model of the object is built, integrating different image features to improve both estimation robustness and precision. All the measurements comi...

We propose a per-frame upper body pose estimation method for sports players captured in low-resolution team sports videos. Using the head-center-aligned upper body region appearance in each frame from the head tracker, our framework estimates (1) 2D spine pose, composed of the head center and the pelvis center locations, and (2) the orientation of the upper body in each frame. Our framework is ...

We present a discriminative deformable part model for the recovery of qualitative pose, inferring coarse pose labels (e.g., left, frontright, back), a task which we expect to be more robust to common confounding factors that hinder the inference of exact 2D or 3D joint locations. Our approach automatically selects parts that are predictive of qualitative pose and trains their appearance and def...

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