Highly paralellized architecture for image motion estimation

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

Volumn 3985 LNCS, Issue , 2006, Pages 75-86

  Díaz, Javier ^a   Ros, Eduardo ^a   Mota, Sonia ^b   Rodriguez Gomez, Rafael ^a  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; DIGITAL SIGNAL PROCESSING; IMAGE ANALYSIS; MOTION ESTIMATION; OPTICAL RESOLVING POWER; REAL TIME SYSTEMS;

FRAME-RATE SEQUENCES; MOTION PROCESSING; OPTICAL FLOW PROCESSING; SYSTEM RESOURCE REQUIREMENTS;

PARALLEL PROCESSING SYSTEMS;

EID: 33749020811     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11802839_11     Document Type: Conference Paper

References (22)

1. Barron, J.L., Fleet, D.J., Beauchemin, S.: Performance of optical-flow techniques. International Journal of Computer Vision, vol. 12, no1, (1994) pp. 43-77.
2. McCane, B., Novins, K., Crannitch D. and Galvin B.: On Benchmarking Optical Flow. Computer Vision and Image Understanding, vol. 84, (2001) pp. 126-143.
3. Liu, H.C., Hong, T.S., Herman, M., Camus, T., and Chellappa, R.: Accuracy vs. Efficiency Trade-offs in Optical Flow Algorithms. Computer Vision and Image Understanding, vol.72, 3, (1998) pp. 271-286.
4. Weber, J. and Malik, J.: Robust computation of optical flow in a multi-scale differential framework. International Journal of Computer Vision, vol. 14, (1995) pp. 67-81.
5. Lim, S., Apostolopoulos, J.G., Gamal, A.E.: Optical flow estimation using temporally oversampled video. IEEE Transactions on Image Processing, vol. 14, 8, (2005) pp. 1074-1087.
6. Lucas, B.D. and Kanade T.: An Iterative Image Registration Technique with an Application to Stereo Vision. Proc. of the DARPA Image Understanding Workshop, (1984), pp. 121-130.
7. Díaz, J., Ros, E., Mota, S., Carrillo, R., Agís, R.: Real time optical flow processing system. Lecture Notes in Computer Science, vol. 3203, (2004) pp.617-626.
8. Díaz, J., Ros, E., Ortigosa, E. M. and Mota, S.:FPGA based real-time optical-flow system. IEEE Transactions on Circuits and Systems for Video Technology, Accepted for publication.
9. Bainbridge-Smith, A. and Lane, R.G.: Determining Optical Flow Using a Differential Method. Image and Vision Computing, vol. 1, (1997) pp. 11-22.
10. Bainbridge-Smith, A. and Lane, R.G.: Measuring Confidence in Optical Flow Estimation. IEE Electronic Letters, vol. 10, (1996) pp. 882-884.
11. Maya-Rueda, S., Arias-Estrada, M.: FPGA Processor for Real-Time Optical Flow Computation. Lecture Notes in Computer Science, vol. 2778, (2003), pp. 1103-1016.
12. Brandt, J.W.: Improved Accuracy in Gradient Based Optical Flow Estimation. Int. Journal of Computer Vision, vol. 25, 1, (1997), pp. 5-22.
13. Simoncelli, E. P.: Design of multi-dimensional derivatives filters. Proc. IEEE International Conf. on Image Processing, Austin Tx, (1994), pp. 790-794.
14. Fleet, D.J. and Langley, K.: Recursive filters for optical flow. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, 1, (1995) pp. 61-67.
15. Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnorr, C.: Variational optical flow computation in real time. IEEE Transactions on Image Processing, vol. 14, 5, (2005) pp. 608-615.
16. Dumontier, C., Luthon, F., Charras, J.P.: Real-time DSP implementation for MRF-based video motion detection. IEEE Transactions on Image Processing, vol. 8, 10, (1999) pp. 1341-1347.
17. Forsell, M. J.: Architectural differences of efficient sequential and parallel computers. Journal of Systems Architecture: the EUROMICRO Journal, vol. 47, 13, (2002) pp. 1017-1041.
18. SRAM ZBT memories, part number: 71T75602. Datasheet available at: www.idt.com.
19. Celoxica company. Web site and products information available at: www.celoxica.com.
20. Horn, B.K.P. and Schunck, B.G.: Determining optical flow. Artificial Intelligent vol. 17, (1981) pp 185-204.
21. Martín, J.L., Zuloaga, A., Cuadrado, C., Lázaro, J., Bidarte, U.: Hardware implementation of optical flow constraint equation using FPGAs. Computer Vision and Image Understanding No. 3, (2005) pp. 462-490.
22. Niitsuma, H. and Maruyama, T.: Real-Time Detection of Moving Objects. Lecture Notes in Computer Science, FPL 2004, vol. 3203, (2004) pp. 1153-1157.