What is usual in unusual videos? trajectory snippet histograms for discovering unusualness
Author
İşcen, Ahmet
Armağan, Anıl
Duygulu, Pınar
Date
2014-06Source Title
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2014
Publisher
IEEE
Pages
808 - 813
Language
English
Type
Conference PaperItem Usage Stats
145
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118
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Abstract
Unusual events are important as being possible indicators of undesired consequences. Moreover, unusualness in everyday life activities may also be amusing to watch as proven by the popularity of such videos shared in social media. Discovery of unusual events in videos is generally attacked as a problem of finding usual patterns, and then separating the ones that do not resemble them. In this study, we address the problem from a different perspective, and try to answer what type of patterns are shared among unusual videos that make them resemble to each other regardless of the ongoing event. With this challenging problem at hand, we propose a novel descriptor to encode the rapid motions in videos utilizing densely extracted trajectories. The proposed descriptor, which is referred to as trajectory snipped histograms, is used to distinguish unusual videos from usual videos, and further exploited to discover snapshots in which unusualness happen. Experiments on domain specific people falling videos and unrestricted funny videos show the effectiveness of our method in capturing unusualness. © 2014 IEEE.
Keywords
DetectionEvent Anomaly
Computer vision
Error detection
Graphic methods
Trajectories
Descriptors
Domain specific
Event Anomaly
Rapid motions
Social media
Anomaly detection
Pattern recognition