A Survey on Nonrigid Object Recognition Approaches and their Applications to Face Detection and Human Body Detection

There is a recent growing interest in recognition of biological individuals in images: human being detection, face detection, animal body recognition are examples of relatively new research areas with important practical applications. From the Computer Vision point of view, humans and animals are nonrigid objects, i.e., objects whose shape can undergo nonrigid geometric transformations. Other nonrigid interesting objects are: robots, tools, vehicles, etc. Nonrigid object recognition is a difficult task and an open research problem in which we need to deal with both the common problems of the rigid case and the variability derived from the degrees of freedom of the nonrigid object’s shape. In this paper we present a survey on the methodological features of the main existing approaches to nonrigid object recognition showing how systems specialized in different domains often share the same techniques. We will focus our attention on the two most important application domains: human body recognition and face detection, which provide most of the scientific proposals concerning nonrigid object recognition.