Face Cyclographs for Recognition

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.

[1]  J William,et al.  IEEE Computer Graphics and Applications , 2019, Computer.

[2]  Eli Peli,et al.  Object Recognition in Man, Monkey and Machine , 1999 .

[3]  Vision Research , 1961, Nature.

[4]  Harry Shum,et al.  Rendering with concentric mosaics , 1999, SIGGRAPH.

[5]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[6]  David Salesin,et al.  Multiperspective panoramas for cel animation , 1997, SIGGRAPH.

[7]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[8]  Shmuel Peleg,et al.  Panoramic mosaics by manifold projection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Paul Rademacher,et al.  Multiple-center-of-projection images , 1998, SIGGRAPH.

[10]  Guodong Guo,et al.  Face, expression, and iris recognition using learning-based approaches: computational recognition of identity and activity , 2008 .

[11]  H. Bülthoff,et al.  Effects of temporal association on recognition memory , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Andrew Davidhazy.  Principles of peripheral photography , 1986 .