VAST: A Human-Centered, Domain-Independent Video Analysis Support Tool
Abstract
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.
Subject
video analysis support toolvideo analysis interface
views
human computer interaction
user study
multi-perspective, location-based context
digital video collection
volleyball videos
Bat Lab videos
Citation
Nordt, Marlo Faye (2008). VAST: A Human-Centered, Domain-Independent Video Analysis Support Tool. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /ETD -TAMU -2008 -12 -92.
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