Model-Based Human Motion Capture from Monocular Video Sequences

Generating motion and capturing motion of an articulated body for computer animation is an expensive and time-consuming task. Conventionally, animators manually generate intermediate frames between key frames, but this task is very labor-intensive. This paper presents a model-based singularity-free automatic-initialization approach to capturing human motion from widely-available, static background monocular video sequences. A 3D human body model is built and projected on a 2D projection plane to find the best fit with the foreground image silhouette. We convert the human motion capture problem into two types of parameter optimization problems: static optimization and dynamic optimization. First, we determine each model body configuration using static optimizations for every input image. Then, to obtain better description of motion, the results from all static optimizations are fed into a dynamic optimization process where the entire sequence of motion is considered for the user-spec...

• Type: Conference
• Year: 2003
• Where: ISCIS
• Authors: Jihun Park, Sangho Park, Jake K. Aggarwal
• Keywords: Human Motions, ISCIS 2003, Static Optimization, User-specified Motion