VAST: A Human-Centered, Domain-Independent Video Analysis Support Tool
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Providing computer-aided support for human analysis of videos has been a battle of extremes. Powerful solutions exist, but they tend to be domain-specific and complex. The user-friendly, simple systems provide little analysis support beyond basic media player functionality. We propose a human-centered, domain-independent solution between these two points. Our proposed model and system, VAST, is based on our experience in two diverse video analysis domains: science and athletics. Multiple-perspective location metadata is used to group related video clips together. Users interact with these clip groups through a novel interaction paradigm ? views. Each view provides a different context by which users can judge and evaluate the events that are captured by the video. Easy conversion between views allows the user to quickly switch between contexts. The model is designed to support a variety of user goals and expertise with minimal producer overhead. To evaluate our model, we developed a system prototype and conducted several rounds of user testing requiring the analysis of volleyball practice videos. The user tasks included: foreground analysis, ambiguous identification, background analysis, and planning. Both domain novices and experts participated in the study. User feedback, participant performance, and system logs were used to evaluate the system. VAST successfully supported a variety of problem solving strategies employed by participants during the course of the study. Participants had no difficulty handling multiple views (and resulting multiple video clips) simultaneously opened in the workspace. The capability to view multiple related clips at one time was highly regarded. In all tasks, except the open-ended portion of the background analysis, participants performed well. However, performance was not significantly influenced by domain expertise. Participants had a favorable opinion of the system?s intuitiveness, ease of use, enjoyability, and aesthetics. The majority of participants stated a desire to use VAST outside of the study, given the opportunity.
Subjectvideo analysis support tool
video analysis interface
human computer interaction
multi-perspective, location-based context
digital video collection
Bat Lab videos
Nordt, Marlo Faye (2008). VAST: A Human-Centered, Domain-Independent Video Analysis Support Tool. Doctoral dissertation, Texas A&M University. Available electronically from
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