TY  - JOUR
T1  - 3D Object-grabbing Hand Tracking based on Depth Reconstruction and Prior Knowledge of Grasp
AU  - Cho, Woojin 
AU  - Park, Gabyong 
AU  - Woo, Woontack 
JO  - Journal of KIISE, JOK
PY  - 2019
DA  - 2019/1/14
DO  - 10.5626/JOK.2019.46.7.673
KW  - computer vision
KW  - hand pose tracking
KW  - model-based optimization
KW  - depth reconstruction
AB  - We propose a real-time 3D object-grabbing hand tracking system based on the prior knowledge of grasping an object. The problem of tracking a hand interacting with an object is more difficult compared to the issue of an isolated hand since it requires consideration of occlusion by an object. Most of the previous studies resort to the insufficient data which lacks the data of occluded hand and the information that the presence of an object may rather be a constraint on the pose of the hand. In the present work, we focused on the sequence of a hand grabbing an object by utilizing prior knowledge about grasp situation. Consequently, an excluded depth data of the hand occluded by the object was reconstructed with proper depth data and a reinitialization process was conducted based on the plausible grasp pose of the human. The effectiveness of the proposed process was verified based on model-based tracker with particle swarm optimization. Quantitative and qualitative experiments demonstrate that the proposed processes can effectively improve the performance of model-based tracker for the object-grabbing hand.