Vector-based monocular 3D pose estimation in handling self-occlusion and foreshortening
Abstract
The paper presented vector-based pose estimation in handling self-occlusion and foreshortening. Vector-based pose estimation basically based on 3D pose estimation from the image of user's motion captured by a monocular camera. Based on the method, a 3D human full body model is constructed. The silhouettes extraction from the image captured is being matched with the projection on a virtual image plane. Multipart alignment will be used to adjust 3D pose of the graphical 3D human full body based on silhouettes extraction. Each of body part alignment will be used to define a set of vector of body part represented as a skeleton model. The obtained model is used to identify the human pose and the associated 3D motion parameters. The vector for each body part is used as 3D pose information to achieve the marker-free interaction in the augmented environment and expected to enhance the tracking accuracy on monocular 3D pose estimation. In future work, this method will be applied for interaction in augmented reality (AR) environment.
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