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Volumn , Issue , 2008, Pages

Modeling complex luminance variations for target tracking

Author keywords

[No Author keywords available]

Indexed keywords

CAMERAS; CLUTTER (INFORMATION THEORY); COMPUTER VISION; END EFFECTORS; LIGHTING; LUMINANCE; OPTICAL FLOWS; VISUAL SERVOING;

EID: 51949099870     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587561     Document Type: Conference Paper
Times cited : (9)

References (14)
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    • J. Blinn. Models of light reflection for computer synthesized pictures. In ACM Conf. on Computer graphics and interactive techniques, SIGGRAPH'77, pages 192.198, San Jose, California, 1977.
  • 3
    • 0034205823 scopus 로고    scopus 로고
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    • June
    • K. Deguchi. A direct interpretation of dynamic images with camera and object motions for vision guided robot control. Int. Journal of Computer Vision, 37(1):7-20, June 2000.
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    • Deguchi, K.1
  • 5
    • 0032179948 scopus 로고    scopus 로고
    • Efficient region tracking with parametric models of geometry and illumination
    • October
    • G. Hager and P. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(10):1025-1039, October 1998.
    • (1998) IEEE Trans. on Pattern Analysis and Machine Intelligence , vol.20 , Issue.10 , pp. 1025-1039
    • Hager, G.1    Belhumeur, P.2
  • 6
    • 0035364933 scopus 로고    scopus 로고
    • Computing optical flow with physical models of brightness variation
    • June
    • H.W. Haussecker and D.J. Fleet. Computing optical flow with physical models of brightness variation. IEEE Trans. on PAMI, 23(6):661-673, June 2001.
    • (2001) IEEE Trans. on PAMI , vol.23 , Issue.6 , pp. 661-673
    • Haussecker, H.W.1    Fleet, D.J.2
  • 7
    • 0019698606 scopus 로고
    • Determining optical flow
    • August
    • B.K.P. Horn and B.G. Schunck. Determining optical flow. Artificial Intelligence, 17(1-3):185-203, August 1981.
    • (1981) Artificial Intelligence , vol.17 , Issue.1-3 , pp. 185-203
    • Horn, B.K.P.1    Schunck, B.G.2
  • 9
    • 0030260990 scopus 로고    scopus 로고
    • Subspace methods for robot vision
    • October
    • S.K. Nayar, S.A. Nene, and H. Murase. Subspace methods for robot vision. IEEE Trans. on Robotics, 12(5):750-758, October 1996.
    • (1996) IEEE Trans. on Robotics , vol.12 , Issue.5 , pp. 750-758
    • Nayar, S.K.1    Nene, S.A.2    Murase, H.3
  • 10
    • 0032166366 scopus 로고    scopus 로고
    • Revised definition of optical flow: Integration of radiometric and geometric cues for dynamic scene analysis
    • S. Negahdaripour. Revised definition of optical flow: Integration of radiometric and geometric cues for dynamic scene analysis. IEEE Trans. on PAMI, 20(9):961-979, 1998.
    • (1998) IEEE Trans. on PAMI , vol.20 , Issue.9 , pp. 961-979
    • Negahdaripour, S.1
  • 11
    • 0016519457 scopus 로고
    • Illumination for computer generated pictures
    • June
    • B.T. Phong. Illumination for computer generated pictures. Communication of the ACM, 18(6):311-317, June 1975.
    • (1975) Communication of the ACM , vol.18 , Issue.6 , pp. 311-317
    • Phong, B.T.1
  • 13
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    • Multiple constraints for optical flow
    • Stockholm, Sweden, May
    • M. Tistarelli. Multiple constraints for optical flow. In 3rd European Conf. on Computer Vision, ECCV'94, volume 1, pages 61-70, Stockholm, Sweden, May 1994.
    • (1994) 3rd European Conf. on Computer Vision, ECCV'94 , vol.1 , pp. 61-70
    • Tistarelli, M.1
  • 14
    • 34250898694 scopus 로고
    • Motion field and optical flow: Qualitative properties
    • May
    • A. Verri and T. Poggio. Motion field and optical flow: qualitative properties. IEEE Trans. on PAMI, 11(5):490-498, May 1989.
    • (1989) IEEE Trans. on PAMI , vol.11 , Issue.5 , pp. 490-498
    • Verri, A.1    Poggio, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.