Learning People’s Appearances from Multiple Views
نویسندگان
چکیده
In this document, a system for recognizing persons in images is proposed. It is based on learning the outer appearance of a person from image sequences. In order to accomplish this, a statistical model of every person, we want to recognize, is being learnt. Positive training data is acquired by using a distributed camera network. Video data is labeled automatically to minimize user interaction. Foreground segmentation is performed to seperate the person of interest from the background. Various features are extracted and combined to form a training data set for each individual. Person recognition is performed by using a multi-scale classifier, that iteratively classifies image parts to create an overall recognition result. Finally, the position of a person in the image is estimated. Experimental results show the system to perform well.
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تاریخ انتشار 2006