Abstract
Content-based retrieval of 3D human motion capture data has significant impact in different fields such as physical medicine, rehabilitation, and animation. This paper develops an efficient indexing approach for 3D motion capture data, supporting queries involving both sub-body motions (e.g., Find similar knee motions) as well as whole-body motions. The proposed indexing structure is based on the hierarchical structure of the human body segments consisting of independent index trees corresponding to each sub-part of the body. Each level of every index tree is associated with the weighted feature vectors of a body segment and supports queries on sub-body motions and also on whole-body motions. Experiments show that up to 97% irrelevant motions can be pruned for any kind of motion query while retrieving all similar motions, and one traversal of the index structure through all index trees takes on an average 15 μsec with the existence of motion variations.
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Pradhan, G.N., Li, C., Prabhakaran, B. (2006). Hierarchical Indexing Structure for 3D Human Motions. In: Cham, TJ., Cai, J., Dorai, C., Rajan, D., Chua, TS., Chia, LT. (eds) Advances in Multimedia Modeling. MMM 2007. Lecture Notes in Computer Science, vol 4351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69423-6_38
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DOI: https://doi.org/10.1007/978-3-540-69423-6_38
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