Human Motion Retrieval Based on Sparse Coding and Touchless Interactions
Liuyang Zhou, Howard W. H. Leung · 2013
To search for a particular motion from a large database, a user-friendly and efficient retrieval mechanism is essential. In this paper, we propose a human motion retrieval system based on sparse coding and touch less interactions. Compared with existing methods that involve vector quantization, sparse coding leads to a more compact and discriminative representation. Motion comparison based on sparse representation greatly improves the effectiveness of motion retrieval in terms of accuracy and speed. With the recent advancement in human motion tracking hardware such as Kinect, our retrieval system allows the user to specify the query motion by performing it directly. Besides, the user interacts with the retrieval system interactively using gestures so no controller is required thus delivering a natural user interface.