LMA-based motion retrieval for folk dance cultural heritage
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Motion capture (mocap) technology is an efficient method for digitizing art-performances, and it is becoming a popular method for the preservation and dissemination of dances. However, stylistic variations of human motion are difficult to measure and cannot be directly extracted from the motion capture data itself. In this work, we present a framework based on Laban Movement Analysis (LMA) that aims to identify style qualities in motion and provides a mechanism for motion indexing using the four LMA components (Body, Effort, Shape, Space), which can also be subsequently used for intuitive motion retrieval. We have designed and implemented a prototype motion search engine in which users can perform queries using motion clips in a folk dance database. Results demonstrate that the proposed method can be used in place, or in combination with text-based queries, to enable more effective and flexible motion database search and retrieval. © Springer International Publishing Switzerland 2014.
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