Recognition by using an active/space-variant sensor

The problem of object recognition is addressed. In the literature this task has been generally considered in a "passive" perspective, where everything is static and there is no definite relation between the object and its environment. We propose an "active" approach for object recognition, based on the capability of the observer to move and give a better description of the object under consideration and also to take advantage of the relations between the objects and the environment. This can be accomplished at the task level and at the sensor level. The face recognition problem, based on the face-space approach, is considered to demonstrate the advantage of adopting an active retina to sample the face, build a database and perform the recognition task. By using an active space-variant retina the size of the database is considerably reduced and consequently the processing time for recognition. A comparative experiment using the active and static approach is presented.<<ETX>>

[1]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[2]  Giulio Sandini,et al.  Dynamic aspects in active vision , 1992, CVGIP Image Underst..

[3]  Yiannis Aloimonos,et al.  Purposive and qualitative active vision , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[4]  Giulio Sandini,et al.  An anthropomorphic retina-like structure for scene analysis , 1980 .

[5]  Peter J. Burt,et al.  `Smart Sensing' in machine vision , 1988 .

[6]  A. L. I︠A︡rbus.  Eye Movements and Vision , 1967 .

[7]  Lawrence Stark.  Top-down vision in humans and robots , 1993, Electronic Imaging.

[8]  Dana H. Ballard,et al.  Animate Vision , 1991, Artif. Intell..

[9]  Giulio Sandini,et al.  Active vision based on space-variant sensing , 1991 .

[10]  L Sirovich,et al.  Low-dimensional procedure for the characterization of human faces. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[11]  W. Eric L. Grimson,et al.  Localizing Overlapping Parts by Searching the Interpretation Tree , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Kjell Brunnström,et al.  Active Detection and Classsification of Junctions by Foveation with a Head-Eye System Guided by the Scale-Space Primal Sketch , 1992, ECCV.