Abstract
Vision research in fields as diverse as computer science, psychology, and neurophysiology, has led to the emergence of stereopsis and kineopsis as the two principal views which explain some of the mechanisms of space perception.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aggarwal, J.K., Davis, L.S., and Martin, W.N., (1982) ‘Correspondence processes in dynamic scene analysis,’ Proc. IEEE, vol. 69, no. 5, pp. 562–572.
Ballard, D.H., and Kimball, O.A., (1983) ‘Rigid body motion from optical flow and depth,’ Computer Vision, Graphics, and Image Processing, vol. 22, pp. 95–115.
Barlow, H.B., Blakemore, C., and Pettigrew, J.D., (1967) ‘The neural mechanism of binocular perception,’ J. Physiology, vol. 193, pp. 327342.
Barnard, S.T., and Thompson, W.B., (1980) ‘Disparity analysis in images,’ IEEE Trans. Pattern Analysis and Machine Intelligence, vol. PAMI-2, pp. 333–340.
Bruss, A.R., and Horn, B.K.P., (1983) ‘Passive navigation,’ Computer Vision, Graphics and Image Processing, vol. 21, pp. 3–20.
Duda, R.O., and Hart, P.E., (1973), Pattern Classification and Scene Analysis, Wiley-Interscience.
Fennema C.L., and Thompson, W.B., (1979) ‘Velocity determination in scenes containing several moving objects,’ Computer Graphics and Image Processing, vol. 9, pp. 301–315.
Gibson, E.J., Gibson J.J., Smith O.W., and Flock, H., (1959) ‘Motion parallax as a determinant of perceived depth,’ J. of Experimental Psychology, vol. 58, pp. 40–51.
Horn, B.K.P., and Schunck, B.G., (1981) ‘Determining optical flow,’ Artificial Intelligence, vol. 17, pp. 185–203.
Gibson, E.J., Gibson J.J., Smith O.W., and Flock, H., (1959) ‘Motion parallax as a determinant of perceived depth,’ J. of Experimental Psychology, vol. 58, pp. 40–51.
Horn, B.K.P., and Schunck, B.G., (1981) ‘Determining optical flow,’ Artificial Intelligence, vol. 17, pp. 185–203.
Horn, B.K.P., and Schunck, B.G., (1981) ‘Determining optical flow,’ Artificial Intelligence, vol. 17, pp. 185–203.
Julesz, B., (1971), Foundations of Cyclopean Perception, University of Chicago Press, Chicago.
Lawton, D.T., and Rieger, J.H., (1983) ‘The use of difference fields in processing sensor motion,’ Proc. Image Understanding Workshop, Washington, D.C., pp. 77–83.
Lelong-Ferrand, J., and Amaudiès, J.M., (1974) Cours de Mathématiques - Tome 3, Géométrie et Cinématique, Dunod, Paris.
Longuet-Higgins, H.C., and Prazdny, K., (1980) ‘The interpretation of a moving retinal image,’ Proc. Royal Society London, vol. B 208, pp. 385–397.
Marr, D., and Poggio, T., (1979) ‘A computational theory of human stereo vision,’ Proc. Royal Society London, vol. B 204, pp. 301–328.
Mitiche, A., (1984) ‘Computation of optical flow and rigid motion,’ Proc. 2nd IEEE Workshop on Computer Vision: Representation and Control, Annapolis, MD.
Mitiche, A., (1984), ‘On combining stereopsis and kineopsis for space perception,’ Proc. IEEE First Conference on Artificial Intelligence Applications, Denver, CO, pp. 156–160.
Nagel, H.-H., (1982) ‘On change detection and displacement estimation in image sequences,’ Pattern Recognition Letters, vol. 1, pp. 55–59.
Nagel, H.-H., (1983) ‘Displacement vectors derived from second-order intensity variation in image sequences,’ Computer Vision, Graphics and Image Processing, vol. 21, pp. 85–117.
Nakayama, K., and Loomis, J.M., (1974) ‘Optical velocity patterns, velocity-sensitive neurons, and space perception: A hypothesis, Perception, vol. 3, pp. 63–80.
Paquin, R., and Dubois, E. (1983) ‘A spatio-temporal gradient method for estimating the displacement field in time-varying imagery,’ Computer Vision, Graphics and Image Processing, pp. 205–221.
Potter, J.L., (1972) ‘Scene segmentation using motion information,’ Computer Graphics and Image Processing, vol. 6, pp. 558–581.
Prazdny, K., (1983) ‘On the information in optical flows,’ Computer Vision, Graphics and Image Processing, vol. 22, pp. 239–259.
Thompson, W.B., (1980) ‘Combining motion and contrast for segmentation,’ IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 2, pp. 543–549, 1980.
Thompson, W.B., and Barnard, S.T., (1981) ‘Lower-level estimation and interpretation of visual motion,’ Computer, vol. 14, pp. 20–28.
Waxman, A.M., (1983) ‘Kinematics of image flow,’ Proc. Image Understanding Workshop, Washington D.C., pp. 175–181.
Wohn, K., Davis, L.S. and Thrift, P., (1983) ‘Motion estimation based on multiple local constraints and nonlinear smoothing,’ Pattern Recognition, vol. 16, no. 6, pp. 563–570.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1988 Kluwer Academic Publishers
About this chapter
Cite this chapter
Mitiche, A. (1988). A Computational Approach to the Fusion of Stereopsis and Kineopsis. In: Martin, W.N., Aggarwal, J.K. (eds) Motion Understanding. The Kluwer International Series in Engineering and Computer Science, vol 44. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1071-6_3
Download citation
DOI: https://doi.org/10.1007/978-1-4613-1071-6_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8413-0
Online ISBN: 978-1-4613-1071-6
eBook Packages: Springer Book Archive