Finding People and Animals by Guided Assembly

This paper describes a new representation for people and animals, called a body plan. The representation is an organized collection of grouping hints obtained from constraints on color, texture, shape, and geometrical relations. Body plans can be learned from image data, using established statistical learning techniques. Body plans are well adapted to segmentation and recognition in complex environments, such as the huge libraries of digitized images now becoming widely available. Two speciic applications of body plans are presented: an algorithm that determines whether an image depicts a scantily clad human and an algorithm that learns and uses a body plan to nd pictures of horses. Both algorithms demonstrate excellent performance on large, poorly controlled input data.