A System for Analyzing and Indexing Human-Motion Databases

Summary: Data-driven motion representation via divisively clustered piecewise-linear models; automatic selection by markers. Indexing via transition trajectories through linear components; supports full/partial motions and compact representations, no time-warping. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3720
Venue: SIGMOD
Year: 2005
Pagerank: 4.1945683e-05
Overall Rank: 12,547 | 12.72%
DOI: -

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Rank	Cited Paper	Year	Venue	Pagerank
3,726	Indexing Large Human-Motion Databases	2004	VLDB	6.8148202e-05

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