MT-Based Motion Annotation and Retrieval

Given a class of semantically related motions, we have derived a class motion template that captures the consistent as well as the inconsistent aspects of all motions in the class. The application of MTs to automatic motion annotation and retrieval, which is the content of this chapter, is based on the following interpretation: the consistent aspects of a class MT represent the class characteristics that are shared by all motions, whereas the inconsistent aspects represent the class variations that are due to different realizations. The key idea in designing a distance measure for comparing a class MT with unknown motion data is to mask out the inconsistent aspects – a kind of class-dependent adaptive feature selection – so that related motions can be identified even in the presence of significant spatio-temporal variations. In Sect. 14.1, we define such a distance measure, which is based on a subsequence variant of DTW. Our concepts of MT-based annotation and retrieval are then described in Sect. 14.2 and Sect. 14.3, respectively, where we also report on our extensive experiments [143, 144]. To substantially speed up the annotation and retrieval process, we introduce an index-based (the index being independent of the class MTs) preprocessing step to cut down the set of candidate motions by using suitable keyframes (Sect. 14.4). In Sect. 14.5, we compare MT-based matching to several baseline methods (based on numerical features) as well as to adaptive fuzzy querying. Finally, related work and future research directions are discussed Sect. 14.6.