Ye Liu, Xinye Zhang, J. Cui, Chen Wu, H. Aghajan, H. Zha
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Visual analysis of child-adult interactive behaviors in video sequences
Kids activity means a lot to their parents, and in the analysis of the activities, video retrieval has played an important role. In this paper, we propose an effective approach for the retrieval of the kid's activities from home videos. The video sequences are taken from our test-bed environment that is designed in the form of a smart home, and feature various types of child-adult interactions. We present a novel retrieval method with two steps, first using spatio-temporal matching to obtain a coarse result, And then we propose a method to learn dominant child-adult interactive behaviors based on a sequence of home videos. Based on these dominant behaviors, we get rid of some false retrieval and obtain fine result. We implement and test our methodology on a newly-introduced dataset containing several types of kid's activities, and the retrieval result shows its potential application in the video analysis demain, it can find out most of the video clips relevant to the query one.