Motion Map: Image-based Retrieval and Segmentation of Motion Data

Abstract

Recent proliferation of motion capture systems enables motion data to be saved as an archive system, and the data are usually extracted by selecting an appropriate file by its name or annotation explaining the content of motions. Such semantic-based retrieval, however, is not suited to unstructured files that include many types of elemental motions, due to the difficulty in giving comprehensible annotations. Moreover, expected motion clips are often included as a part of entire sequences, and the data therefore should be manually clipped using some authoring tools. This paper proposes an image-based user interface for retrieving motion data using a self-organizing map for supplying recognizable icons of postures. The postures are used as keys for retrieval, and the desirable segments of the motion data can be accurately extracted by specifying their starting and ending postures. The number of possible motion segments is flexibly controlled by changing the scope of postures used as the keys.