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Ramin Zabih

Assistant Professor

PhD Stanford, 1994

My work in the field of computer vision covers both basic research issues and a range of new applications. I have worked on a number of issues in early vision, including image restoration, visual correspondence, and motion-based tracking. My recent work with Y. Boykov and O. Veksler provides novel algorithms for a fundamental class of vision problems whose previous solutions required exponential time. Our results rely on the application of recent results from graph theory, which can provide efficient algorithms that generate provably good answers.

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I am also exploring a number of different applications of computer vision, with an emphasis on automating visual tasks. One of the most important applications is in the area of content-based access to image databases. While large collections of digital imagery are becoming commonplace, the tools available for accessing image databases are still quite primitive. My past work with G. Pass and with J. Huang et al. focused on this problem for collections of static images. In ongoing research, V. Kettnaker and I are addressing the issue for video, where we hope to exploit some insights about the role of contextual information in the human visual system. I am also working with Microsoft on automating some visual tasks that occur in the development of programs with graphical user interfaces.

Professional Activities

Program Committee, ACM Conf. on Multimedia.


  • A combinatorial approach to early vision. Microsoft Research, Dec. 1997.

  • ___. Computer Science, Dartmouth, April 1998.


  • Automatic hierarchical color image classification. Proc. ACM Conf. Multimedia, Bristol, England, Aug. 1998 (with J. Huang and R. Kumar).

  • Markov random fields with efficient approximations. Proc. IEEE Computer Vision and Pattern Recognition Conf., Santa Barbara, California, June 1998 (with Y. Boykov and O. Veksler).