3D Pose Tracking Using a Recovered 3D Model

摘要

Template warping is a widely used approach in the pose recovery field. Due to its flexibility, template warping is especially useful in monocular video motion tracking. Tracking accuracy is largely determined by the appearance of the 3D model. Moreover, the appearance of the 3D model plays a very important role in template warping. However, accurate tracking results are difficult to obtain because hand estimated 3D models are prone to inaccuracies (the appearance of 3D models is commonly initialized by the user based on the first frame of video footage; the result is a hand estimated 3D model). In order to overcome this problem, we propose an iterative optimization process that estimates the appearance of the 3D model during tracking. Our results show that our proposed 3D model estimation achieves better performance than the hand model initialization estimation.