Face Cyclographs for Recognition

Abstract

A new representation of faces, called face cyclographs, is introduced for face recognition that incorporates all views of a rotating face into a single image. The main motivation for this representation comes from recent psychophysical studies that show that humans use continuous image sequences in object recognition. Face cyclographs are created by slicing spatiotemporal face volumes that are constructed automatically based on real-time face detection. This representation is a compact, multiperspective, spatiotemporal description. To use face cyclographs for recognition, a dynamic programming based algorithm is developed. The motion trajectory image of the eye slice is used to analyze the approximate single-axis motion and normalize the face cyclographs. Using normalized face cyclographs can speed up the matching process. Experimental results on more than 100 face videos show that this representation efficiently encodes the continuous views of faces and improves face recognition performance over view-based methods.