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Optical flow using color information: preliminary results

Published:16 March 2008Publication History

ABSTRACT

Optical flow cannot be completely determined only from brightness information of images, without introducing some assumptions about the nature of movements in the scene. Color is an additional natural source of information that facilitates the solution of this problem. This work aims to illustrate the improvement in the optical flow estimation by using color information through experimental results.

References

  1. J. Barron and R. Klette. Quantitative color optical flow. In 16th International Conference on Pattern Recognition, volume 4, pages 251--255, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J.-Y. Bouguet. Pyramidal implementation of the Lucas Kanade feature tracker. OpenCV Documentation, Intel Corporation, Microprocessor Research Lab, 1999.Google ScholarGoogle Scholar
  3. E. M. d. O. Caldeira. Navegação Reativa de Robôs Móveis com Base no Fluxo Óptico. PhD thesis, UFES, Vitória, ES, Dec. 2002.Google ScholarGoogle Scholar
  4. H. Farid and E. P. Simoncelli. Differentiation of discrete multi-dimensional signals. IEEE Transactions on Image Processing, 13(4):496--508, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. M. Gokstorp and P.-E. Danielsson. Velocity tuned generalized sobel operators for multiresolution computation of optical flow. In IEEE International Conference on Image Processing, volume 2, pages 765--769, Austin, TX, USA, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  6. P. Golland and A. M. Bruckstein. Motion from color. Computer Vision and Image Understanding: CVIU, 68(3):346--362, Dec. 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. B. Horn and B. Schunck. Determining optical flow. Artificial Intelligence, 16(1--3):185--203, August 1981.Google ScholarGoogle Scholar
  8. B. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In IJCAI81, pages 674--679, 1981.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. H. N. Machado and G. A. S. Pereira. Medição das velocidades de um robô móvel utilisando sequências de imagens de sua superfície de movimentação. In XVI Congresso Brasileiro de Automática, pages 1025--1030, Salvador, BA, Brazil, Sept. 2006.Google ScholarGoogle Scholar
  10. N. Ohnishi and A. Imiya. Dominant plane detection from optical flow for robot navigation. Pattern Recognition Letters, 27(9):1009--1021, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. N. Ohta. Optical flow detection by color images. IEEE International Conference On Image Processing, pages 801--805, Sept. 1989.Google ScholarGoogle Scholar
  12. N. Ohta and S. Nishizawa. How much does color information help optical flow computation? IEICE Transactions on Information and Systems - Oxford Journal, 5:1759--1762, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. M. Sarcinelli-Filho, H. A. Schneebeli, and E. M. O. Caldeira. Cálculo do fluxo Óptico em tempo real e sua utilização na navegação de robôs móveis. In V Simpósio Brasileiro de Automação Inteligente, Canela, RS, Brazil, Nov. 2001.Google ScholarGoogle Scholar
  14. J. Shin, S. Kim, S. Kang, S.-W. Lee, J. Paik, B. Abidi, and M. Abidi. Optical flow-based real-time object tracking using non-prior training active feature model. Real-Time Imaging, 11(3):204--218, June 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. E. P. Simoncelli. Design of multi-dimensional derivative filters. In IEEE International Conference on Image Processing, volume 1, pages 790--794, 1994.Google ScholarGoogle ScholarCross RefCross Ref
  16. M. Tagliasacchi. A genetic algorithm for optical flow estimation. Image and Vision Computing, In Press, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          SAC '08: Proceedings of the 2008 ACM symposium on Applied computing
          March 2008
          2586 pages
          ISBN:9781595937537
          DOI:10.1145/1363686

          Copyright © 2008 ACM

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          Publication History

          • Published: 16 March 2008

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