Abstract
Contents-based retrieval of multimedia information has been investigated in several research projects. In this paper, we will focus on an automatic indexing method for human motion data. We convert a motion data, which is represented as time series of 3-D position, into a symbol sequence. We call this method as conversion automatic indexing. The automatic indexing is performed in a pattern matching approach. Reference patterns are necessary for pattern matching, so that we will propose two methods to define primitive motions in order to make reference patterns. The first method divides motion data into segmental motion data by detecting the change of motion speed. The second method classifies segmental motions such that similar segmental motions are gathered in the same cluster. In order to evaluate the similarity between two segmental motions, we use the Dynamic Time Warping (DTW) method because each segmental motion takes different time length even if the same person performed the same motions. Motion data can be converted into a symbol sequence which represents a sequence of primitive motions. Then, Continuous Dynamic Programming (CDP) method is used to recognize contents of motion. CDP is one of the extensions of DTW. It makes us possible to recognize a motion with ease even if it is complex.
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Osaki, R., Shimada, M., Uehara, K. (2000). A Motion Recognition Method by Using Primitive Motions. In: Arisawa, H., Catarci, T. (eds) Advances in Visual Information Management. VDB 2000. IFIP — The International Federation for Information Processing, vol 40. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35504-7_8
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DOI: https://doi.org/10.1007/978-0-387-35504-7_8
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