Active shape models—their training and application
Computer Vision and Image Understanding
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
Leveraging context to resolve identity in photo albums
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Control structures for incorporating picture-specific context in image interpretation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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People are among the most popular subjects in photography, and in many social settings, images of groups of people are captured. People often arrange themselves in a very structured manner in these group images. For example, taller peoplemight stand in a row behind smaller people. This structure is often exploited in captions that sequentially label the individuals in each row. We present an algorithm for automatically finding rows of people in group images. A graph is defined for the image, where each face is a vertex. Energy terms are learned from a training set of images. A minimum cut on this graph defines the rows of people in the image. On our test set, the algorithm achieves perfect results with 67.5% of the images. Detecting rows of people is useful for a number of applications.