Video Diff: Highlighting Differences Between Similar Actions in Video (Siggraph Asia 2015)
Guha Balakrishnan Frédo Durand John Guttag
Example of output frames of our method for a basketball sequence. We overlay the edges of one video over the frames of the second
video. The edges are colored to signify regions of dissimilarity (red being most dissimilar, yellow being least). The overlay is meant to help a
user quickly identify differences in motion between pairs of video that look very similar.
Abstract
When looking at videos of very similar actions with the naked eye,
it is often difficult to notice subtle motion differences between them.
In this paper we introduce video diffing, an algorithm that highlights
the important differences between a pair of video recordings
of similar actions. We overlay the edges of one video onto the
frames of the second, and color the edges based on a measure of
local dissimilarity between the videos. We measure dissimilarity
by extracting spatiotemporal gradients from both videos and calculating
how dissimilar histograms of these gradients are at varying
spatial scales. We performed a user study with 54 people to compare
the ease with which users could use our method to find differences.
Users gave our method an average grade of 4.04 out of
5 for ease of use, compared to 3.48 and 2.08 for two baseline approaches.
Anecdotal results also show that our overlays are useful
in the specific use cases of professional golf instruction and analysis
of animal locomotion simulations.
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