Combining automated and interactive visual analysis of biomechanical motion data

Scott Spurlock, Remco Chang, Xiaoyu Wang, George Arceneaux IV, Daniel F. Keefe, Richard Souvenir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion of, e.g., pigs chewing or bats flying, can be enhanced by providing investigators with a multi-view interface that allows interaction across multiple modalities and representations. In this paper, we employ nonlinear dimensionality reduction to automatically learn a low-dimensional representation of the data and hierarchical clustering to learn patterns inherent within the motion segments. Our multi-view framework allows investigators to simultaneously view a low-dimensional embedding, motion segment clustering, and 3D visual representation of the data side-by-side. We describe an application to a dataset containing thousands of frames of high-speed, 3D motion data collected over multiple experimental trials.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 6th International Symposium, ISVC 2010, Proceedings
Number of pages10
EditionPART 2
StatePublished - 2010
Event6th International, Symposium on Visual Computing, ISVC 2010 - Las Vegas, NV, United States
Duration: Nov 29 2010Dec 1 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6454 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other6th International, Symposium on Visual Computing, ISVC 2010
Country/TerritoryUnited States
CityLas Vegas, NV


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