Accuracy vs. Efficiency trade-offs in optical flow algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1065, Issue , 1996, Pages 174-183

  Liu, Hongche ^a,b   Hang, Tsai Hong ^b   Herman, Martin ^b   Chellappa, Rama ^a  

^a UNIVERSITY OF MARYLAND   (United States)

^b NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84957885333     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-61123-1_137     Document Type: Conference Paper

References (40)

1. Allen, P., Timcenko, A., Yoshimi, B. and Michelman, P., “Automated Tracking and Grasping of a Moving Object with a Robotic Hand-Eye System”, IEEE Transactions on Robotics and Automations, vol. 9, no. 2, pp. 152-165,1993.
2. Ancona, N. and Poggio, T., “Optical Flow from 1-D Correlation: Applications to a Simple Time-to-Crash Detector”, Proceedings of IEEE International Conference on Computer Vision, Berlin, Germany, pp. 209-214,1993.
3. Artieri, A. and Jutand, F., “A Versatile and Powerful Chip for Real-Time Motion Estimation”, Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, Glasgow, UK, pp. 2453-2456, 1989.
4. Barron, J. L., Fleet, D. J. and Beauchemin, S. S., “Performance of Optical Flow Techniques”, International Journal of Computer Vision, vol. 12, no. 1, pp. 43-77,1994.
5. Bober, M. and Kittler, J., “Robust Motion Analysis”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Seattle, WA, pp. 947-952, 1994.
6. Bulthoff, H., Little, J. and Poggio, T., “A Parallel Algorithm for Real-Time Computation of Optical Flow”, Nature, vol. 337, pp. 549-553,1989.
7. Camus, T., “Calculating Time-to-Contact Using Real-Time Quantized Optical Flow”, NISTIR-5609, Gaithersburg, MD, 1995.
8. Camus, T., “Real-Time Quantized Optical Flow”, Proceedings of IEEE Conference on Computer Architectures for Machine Perception, Como, Italy, 1995.
9. Coombs, D., Herman M., Hong T. and Nashman, M., “Real-time Obstacle Avoidance Using Central Flow Divergence and Peripheral Flow”, Proceedings of IEEE International Conference on Computer Vision, Cambridge, MA, 1995.
10. Delbruck, T., “Silicon Retina with Correlation-Based Velocity-Tuned Pixels”, IEEE Transactions on Neural Networks, vol. 4, no. 3, pp. 529-541,1993.
11. Ens, J. and Li, Z.N., “Real-Time Motion Stereo”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 130-135, New York, NY, 1993.
12. Etienne-Cummings, R., Fernando, S.A., Van der Spiegel, J. and Mueller, P., “Real-Time 2D Analog Motion Detector VLSI Circuit”, Proceedings of IEEE International Joint Conference on Neural Networks, vol. 4, pp. 426-431, New York, NY, 1992.
13. Fleet, D.J. and Jepson, A.L., “Computation of Component Image Velocity from Local Phase Information”, International Journal of Computer Vision, vol. 5, no. 1, pp. 77-104,1990.
14. Heeger, D. J. “Optical How Using Spatiotemporal Filters”, International Journal of Computer Vision, vol. 1, no. 4, pp. 279-302,1988.
15. Inoue, H., Tachikawa, T. and Inaba, M., “Robot Vision System with a Correlation Chip for Real-Time Tracking, Optical Flow and Depth Map Generation”, Proceedings IEEE Conference on Robotics and Automation, Nice, France, vol. 2, pp. 1621-1626,1992.
16. Koch, C., Marroquin, J. and Yuille, A., “Analog ‘Neural’ Networks in Early Vision”, Proceedings of the National Academy of Sciences, vol. 83, pp. 4263-4267,1986.
17. Lee, J.C., Sheu, B. J., Fang, W.C. and Chellappa, R., “VLSI neuroprocessors for Video Motion Detection”, IEEE Transactions on Neural Networks, vol. 4, no. 2, pp. 178-191,1993.
18. Liu, H., Hong, T., Herman, M. and Chellappa, R., “A General Motion Model and Spatio-temporal Filters for Computing Optical Flow”, University of Maryland TR-3365, November, 1994; NIST-IR 5539, Gaithersburg MD, January, 1995, to appear in International Journal of Computer Vision.
19. Liu, H., “A General Motion Model and Spatio-temporal Filters for 3-D Motion Interpretations”, PH.D. Dissertation, University of Maryland, September, 1995.
20. Matteucci, P., Regazzani, C.S. and Foresti, G.L., “Real-Time Approach to 3-D Object Tracking in Complex Scenes”, Electronics Letters, vol. 30, no. 6, pp. 475-477,1994.
21. Mioni, A., “VLSI Vision Chips Homepage”, http://www.eleceng.adelaide.edu.au/Groups/GAAS/Bug-eye/visionchips.
22. Mioni, A., Bouzerdoum, A., Yakovleff, A., Abbott, D., Kim, O., Eshraghian, K. and Bogner, R.E., “An Analog Implementation of Early Visual Processing in Insects”, Proceedings International Symposium on VLSI Technology, Systems, and Applications, pp. 283-287, 1993.
23. Moore, A. and Koch C., “A Multiplication Based Analog Motion Detection Chip”, Proceedings of the SPIE, vol. 1473, Visual Information Processing: From Neurons to Chips, pp. 66-75, 1991.
24. Nashman, M., Rippey, W., Hong, T.-H. and Herman, M„ “An Integrated Vision Touch-Probe System for Dimensional Inspection Tasks”, NISTIR 5678, National Institute of Standards and Technology, 1995.
25. Nelson, R., “Qualitative Detection of Motion by a Moving Observer”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Lahaina, HI, pp. 173-178, 1991.
26. Nesi, P., DelBimbo, A.D. and Ben-Tzvi, D. “A Robust Algorithm for Optical Flow Estimation”, Computer Vision and Image Understanding, vol. 62, no. 1, pp. 59-68,1995.
27. Nishihara, H.K., “Real-Time Stereo-and Motion-Based Figure Ground Discrimination and Tracking Using LOG Sign Correlation”, Conference Record of the Twenty-Seventh Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 95-100,1993.
28. Patterson, D. and Hennessy, J., “Computer Organization and Design: the Hardware/Software Interface”, Morgan Kaufman, San Mateo, CA 1994.
29. Rangachar, R., Hong, T.-H., Herman, M., and Luck, R. “Three Dimensional Reconstruction from Optical Flow Using Temporal Integration”, Proceedings of SPIE Advances in Intelligent Robotic Systems: Intelligent Robots and Computer Vision, Boston, MA, 1990.
30. Schunck, B., “Image Flow Segmentation and Estimation by Constraint Line Clustering”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 11, no.10, pp. 1010-1027, 1989.
31. Singh, A., “Optical Flow Computation: A Unified Perspective”, IEEE Computer Society Press, 1991.
32. Smith, S.M., “ASSET-2 Real-Time Motion Segmentation and Object Tracking”, Proceedings of the Fifth International Conference on Computer Vision, pp. 237-244, Cambridge, MA, 1995.
33. Tanner J. and Mead C., “A Correlating Optical Motion Detector”, MIT Advanced Research in VLSI, pp. 57-64, 1984.
34. Tanner, J. and Mead, C., “An Integrated Analog Optical Motion Sensor”, VLSI Signal Processing II, R.W. Brodersen and H.S. Moscovitz, Eds., pp. 59-87, New York, 1988.
35. Waxman, A.M., Wu J. and Bergholm F. “Convected Activation Profiles and Receptive Fields for Real Time Measurement of Short Range Visual Motion”, Proceedings of IF.F.F. Conference on Computer Vision and Pattern Recognition, Ann Arbor, MI, pp. 717-723, 1988.
36. Weber, J. and Malik, J., “Robust Computation of Optical Flow in a Multi-Scale Differential Framework”, Proceedings of the Fourth International Conference on Computer Vision, Berlin, Germany, 1993.
37. Weber, J. and Malik, J., “Robust Computation of Optical Flow in a Multi-Scale Differential Framework”, International Journal of Computer Vision, vol. 14, pp. 67-81, 1995.
38. Weiss, P. and Christensson, B., “Real Time Implementation of Subpixel Motion Estimation for Broadcast Applications”, IEE Colloquim on Applications of Motion Compensation, London, UK, no. 128, pp. 7/ 1-3,1990.
39. Woodfill, J. and Zabin, R., “An Algorithm for Real-Time Tracking of Non-Rigid Objects”, Proceedings of the Ninth National Conference on Artificial Intelligence, pp. 718-723, 1991.
40. Yagi, Y., Kawato, S. and Tsuji, S., “Real-Time Omnidirectional Image Sensor (COPIS) for Vision-Guided Navigation”, IEEE Transactions on Robotics and Automation, vol. 10, no. 1, pp. 11-22, 1994.