Robust head tracking using hybrid color and 3D under natural and unspecified environments
Gwang-Myung Kim, Sungho Yoon, Jung-Hyun Kim, Gi Taek Hur · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
We present a crossbreed feature-based head tracking technique in natural and unspecified environment. Kalman filter is a famous estimation technique in many areas to predict the route of moving object. We tested and developed a Kalman filter to track unpredictable and fast moving objects. Depth information could generate robust tracking result that is little affected by background texture and color. However this is also limited by selected conditions like distance, accuracy of stereo camera, and object occlusion at same distance, etc. To overcome these restrictions, we combined multiple features together into single tracking system that does largely depend on depth feature. We consider multi people environment with rapid walking path.