VACA: a tool for qualitative video analysis

Authors:
Brandon Burr
Affiliations:
Stanford University, Stanford, CA
Venue:
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Year:
2006

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Abstract

In experimental research the job of analyzing data is an extremely slow and laborious process. In particular, video and audio data of human behavior are particularly difficult to analyze, as this type of information does not lend itself to automation. Here we present VACA, an open source tool for qualitative video analysis. VACA presents video annotations on a timeline interface and integrates external sensor data to improve the rate at which analysis can be performed. A comparative study is run against traditional video analysis tools, and results are reported.