A FRAMEWORK FOR MARKERLESS FULL BODY HUMAN 3D MONOCULAR POSE ESTIMATION - TOMI, AZF AR (2014)
Pose estimation IS an important pre-processing step m computer vision-based automatic capture and analysis human motion. Despite its high efficiency in handling the ambiguities situation, multiple view approach of pose estimation is costly incurs high computational cost due to more complex system. Recently, most of the work focusing in a low cost and practical monocular view approach due to its suitability for a common user and low complex system. However, several monocular view issues arise with regard to self-occlusion which leads into problem in body part extraction, and the undetermined value in human pose reconstruction focusing on upper and lower limbs reconstruction that caused the reconstruction problem especially in high noise movement. Thus, this thesis project presents a framework for a real time markerless motion capture to track human full-body movement for monocular 3D pose estimation. The proposed framework comprises of a combination of top-dov.'!1 and bottom-up approach toward 3D pose estimation in monocular view based on endeffector driven. The proposed framework is built as a three-stage framework.