Using Group Prior to Identify People in Consumer Images

While face recognition techniques have rapidly advanced in the last few years, most of the work is in the domain of security applications. For consumer imaging applications, person recognition is an important tool that is useful for searching and retrieving images from a personal image collection. It has been shown that when recognizing a single person in an image, a maximum likelihood classifier requires the prior probability for each candidate individual. In this paper, we extend this idea and describe the benefits of using a group prior for identifying people in consumer images with multiple people. The group prior describes the probability of a group of individuals appearing together in an image. In our application, we have a subset of ambiguously labeled images for a consumer image collection, where we seek to identify all of the people in the collection. We describe a simple algorithm for resolving the ambiguous labels. We show that despite errors in resolving ambiguous labels, ...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Andrew C. Gallagher, Tsuhan Chen
• Keywords: Ambiguous Labels, Computer Vision, Consumer Image Collection, CVPR 2007, Face Recognition Techniques, Personal Image Collection, Prior Probability