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 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 commonly used video analysis tools, and results are reported. Keywords Video analysis, annotation, behavioral research.