Efficient Motion Retrieval in Large Motion Databases

Loading...
Thumbnail Image
Penn collection
Center for Human Modeling and Simulation
Degree type
Discipline
Subject
motion capture
laban movement analysis
indexing
retrieval
Computer Sciences
Engineering
Graphics and Human Computer Interfaces
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Kapadia, Mubbasir
Chiang, I-kao
Thomas, Tiju
Contributor
Abstract

There has been a recent paradigm shift in the computer animation industry with an increasing use of pre-recorded motion for animating virtual characters. A fundamental requirement to using motion capture data is an efficient method for indexing and retrieving motions. In this paper, we propose a flexible, efficient method for searching arbitrarily complex motions in large motion databases. Motions are encoded using keys which represent a wide array of structural, geometric and, dynamic features of human motion. Keys provide a representative search space for indexing motions and users can specify sequences of key values as well as multiple combination of key sequences to search for complex motions. We use a trie-based data structure to provide an efficient mapping from key sequences to motions. The search times (even on a single CPU) are very fast, opening the possibility of using large motion data sets in real-time applications.

Advisor
Date of presentation
2013-01-01
Conference name
Center for Human Modeling and Simulation
Conference dates
2023-05-17T12:42:37.000
Conference location
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation
Collection