NON-RIGID MULTI-BODY TRACKING IN RGBD STREAMS
- 1College of Land Science and Technology, China Agricultural University, Beijing 100083, China
- 2Department of Computer Science, Stevens Institute of Technology, NJ 07030, USA
- 3Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro(PD) 35020, Italy
Keywords: Non-rigid, Multi-body tracking, RGBD, Point clouds
Abstract. To efficiently collect training data for an off-the-shelf object detector, we consider the problem of segmenting and tracking non-rigid objects from RGBD sequences by introducing the spatio-temporal matrix with very few assumptions – no prior object model and no stationary sensor. Spatial temporal matrix is able to encode not only spatial associations between multiple objects, but also component-level spatio temporal associations that allow the correction of falsely segmented objects in the presence of various types of interaction among multiple objects. Extensive experiments over complex human/animal body motions with occlusions and body part motions demonstrate that our approach substantially improves tracking robustness and segmentation accuracy.