3D motion retrieval with motion index tree
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
Automated extraction and parameterization of motions in large data sets
ACM SIGGRAPH 2004 Papers
Proceedings of the 2004 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Efficient content-based retrieval of motion capture data
ACM SIGGRAPH 2005 Papers
Motion templates for automatic classification and retrieval of motion capture data
Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation
Indexing large human-motion databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Information Retrieval for Music and Motion
Information Retrieval for Music and Motion
Emulating human perception of motion similarity
Computer Animation and Virtual Worlds - CASA'2008 Special Issue
Perceptually consistent example-based human motion retrieval
Proceedings of the 2009 symposium on Interactive 3D graphics and games
Indexing and Retrieving Motions of Characters in Close Contact
IEEE Transactions on Visualization and Computer Graphics
Spatial relationship preserving character motion adaptation
ACM SIGGRAPH 2010 papers
Multiscale motion saliency for keyframe extraction from motion capture sequences
Computer Animation and Virtual Worlds
Characterizing structural relationships in scenes using graph kernels
ACM SIGGRAPH 2011 papers
Human Motion Retrieval from Hand-Drawn Sketch
IEEE Transactions on Visualization and Computer Graphics
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In this paper, we propose a new method to index and retrieve animation scenes in which multiple characters closely interact with one another. Such a technique can be an important tool for animators when they want to automatically extract the desired scene from a large database of animation sequence. Existing methods for single character movements do not scale well for multiple characters as they do not take into account the interaction of different body parts. In this paper, we propose a new distance function that computes the similarity of two-character interations using the spatial relationship of the body parts. For each interaction, we produce a time-varying graph structure based on the proximity of different joints, and compute the similarity of interactions by comparing the topology and Laplacian coordinates of the time-varying graph. Experimental results show that the proposed method outperforms previous methods which are based on the kinematics of individual characters. The top retrieved samples are found similar in high level semantics while containing style variations. © 2012 Wiley Periodicals, Inc.