Exploratory Procedure for Computer Vision

This paper deals with Exploratory Procedures for Computer Vision. The assumptions are that we have a mobile camera system with controllable focus, close/open aperture, and ability of recording its position, orientation and movement. Furthermore we assume an unknown and unstructured environment. For our analysis we consider two types of illumination sources: the point source and the extended sky-like source. The exploratory procedures determine the illumination energy, in some cases the illumination orientation, the albedo and the differentiation between the true 3D scene and its picture. The key idea is the mobile active observer. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-88-92. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/772 EXPLORATORY PROCEDURE FOR COMPUTER VISION Ruzena Bajcsy, K. Wohn and S. W. Lee MS-CIS-88-92 GRASP LAB 165 Department of Computer and Information Science School of Engineering and Applied Science University of Pennsylvania Philadelphia, PA 191 04 November 1988 Acknowledgements: This research was supported in part by DARPA grants NO001 4-85K-0018, NO001 4-88-K-0632, U.S Postal Service contract 104230-87-H0001 IM-0195, NSF grants MCS-8219196-CER, IR184-10413-A02 and U.S. Army grants DAA29-84-K-0061, DAA29-84-9-0027. Exploratory Procedure for Computer Vision Ruzena Bajcsy K. Wohn S.W. Lee Computer and Informations Science Department University of Pennsylvania Philadelphia, PA 19104

[1]  Jr. Kenneth Robert Sloan,et al.  World model driven recognition of natural scenes. , 1977 .

[2]  Allen M. Waxman,et al.  Surface Structure and Three-Dimensional Motion from Image Flow Kinematics , 1985 .

[3]  B K Horn,et al.  Calculating the reflectance map. , 1979, Applied optics.

[4]  Allen M. Waxman,et al.  Contour Evolution, Neighborhood Deformation, and Global Image Flow: Planar Surfaces in Motion , 1985 .

[5]  Yiannis Aloimonos,et al.  Active vision , 2004, International Journal of Computer Vision.

[6]  Kenneth J. Turner,et al.  Computer perception of curved objects using a television camera , 1974 .

[7]  Ruzena Bajcsy,et al.  Texture gradient as a depth cue , 1976 .

[8]  Alex Pentland,et al.  Local Shading Analysis , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Berthold K. P. Horn.  Robot vision , 1986, MIT electrical engineering and computer science series.

[10]  Berthold K. P. Horn,et al.  Determining lightness from an image , 1974, Comput. Graph. Image Process..

[11]  D. Blostein.  Recovering the orientation of textured surfaces in natural scenes (image processing) , 1987 .

[12]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[13]  Dana H. Ballard,et al.  ACTIVE NAVIGATION: TRACKING AN ENVIRONMENTAL POINT CONSIDERED BENEFICIAL. , 1986 .

[14]  H. C. Longuet-Higgins,et al.  The interpretation of a moving retinal image , 1980, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[15]  Katsushi Ikeuchi,et al.  Determining Surface Orientations of Specular Surfaces by Using the Photometric Stereo Method , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  A. Pentland.  Finding the illuminant direction , 1982 .

[17]  Berthold K. P. Horn.  SHAPE FROM SHADING: A METHOD FOR OBTAINING THE SHAPE OF A SMOOTH OPAQUE OBJECT FROM ONE VIEW , 1970 .