Automated Gesture Segmentation From Dance Sequences

Complex human motion (e.g. dance) sequences are typically analyzed by segmenting them into shorter motion sequences, called gestures. However, this segmentation process is subjective, and varies considerably from one choreographer to another. Dance sequences also exhibit a large vocabulary of gestures. In this paper, we propose an algorithm called Hierarchical Activity Segmentation. This algorithm employs a dynamic hierarchical layered structure to represent human anatomy, and uses lowlevel motion parameters to characterize motion in the various layers of this hierarchy, which correspond to different segments of the human body. This characterization is used with a na

• Type: Conference
• Year: 2004
• Where: FGR
• Authors: Kanav Kahol, Priyamvada Tripathi, Sethuraman Panchanathan
• Keywords: Biometrics, Complex Human Motion, FGR 2004, Motion Sequences, Shorter Motion Sequences