Compositional object pattern: a new model for album event recognition
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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We explore event recognition in the personal photo album setting where the task is not to identify event in individual photo but in the whole album. This setting arises from the way people organize their own collections and the fact that individual photo in these albums often fails to convey meaningful event semantic behind the the album. We work on this problem in a object-centric manner, i.e. we train detectors for objects relevant to the events in the holiday dataset we built, and then detect these holidays based on object detector outputs. The prior knowledge, i.e. what objects are relevant to the event, is obtained statistically from mass image collection web site and thus tends to be more accurate and less biased.