This paper presents a novel and fast scheme to detect different body parts in human motion. Using monocular video sequences, trajectory estimation and body modeling of moving humans are combined in a co-operating processing architecture. More specifically, for every individual person, features of body ratio, silhouette and appearance are integrated into a hybrid model to detect body parts. The conventional assumption of upright body posture is not required. We also present a new algorithm for accurately finding the center point of the human body. The body configuration is finally described by a skeleton model. The feasibility and accuracy of the proposed scheme are analyzed by evaluating its performance for various sequences with different subjects and motion types (walking, pointing, kicking, leaping and falling). Our detection system achieves nearly real-time performance (around 10 frames/second).
|Title of host publication||Proceedings of the 5th International Conference Articulated Motion and Deformable Objects, ADMO 2008, July 9-11, 2008, Mallorca, Spain|
|Editors||F.J. Perales, R.B. Fisher|
|Place of Publication||Berlin|
|Publication status||Published - 2009|
|Name||Lecture Notes in Computer Science|