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Efficient Depth Edge Detection Using Structured Light

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Advances in Visual Computing (ISVC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3804))

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Abstract

This research features a novel approach that efficiently detects depth edges in real world scenes. Depth edges play a very important role in many computer vision problems because they represent object contours. We strategically project structured light and exploit distortion of the light pattern in the structured light image along depth discontinuities to reliably detect depth edges. Distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. For practical application of the proposed approach, we have presented methods that guarantee the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show that the proposed method accurately detects depth edges of human hand and body shapes as well as general objects.

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References

  1. Cass, T.A.: Robust Affine Structure Matching for 3D Object Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1264–1265 (1998)

    Google Scholar 

  2. Weiss, I., Ray, M.: Model-based recognition of 3D object from single vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 116–128 (2001)

    Google Scholar 

  3. Frohlinghaus, T., Buhmann, J.M.: Regularizing phase-based stereo. In: Proceedings of 13th International Conference on Pattern Recognition, pp. 451–455 (1996)

    Google Scholar 

  4. Lee, S.H., Choi, J.M., Kim, D.S., Jung, B.C., Na, J.K., Kim, H.M.: An Active 3D Robot Camera for Home Environment. In: Proceedings of 4th IEEE Sensors Conference (2004)

    Google Scholar 

  5. Scharstein, D., Szeliski, R.: High-Accuracy Stereo Depth Maps Using Structured Light. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 195–202 (2003)

    Google Scholar 

  6. Raskar, R., Tan, K.H., Feris, R., Yu, J., Turk, M.: Non-photorealistic Camera: Depth Edge Detection and Stylized Rendering Using Multi-Flash Imaging. In: Proceedings of ACM SIGGRAPH Conference, vol. 23, pp. 679–688 (2004)

    Google Scholar 

  7. Feris, R., Turk, M., Raskar, R., Tan, K., Ohashi, G.: Exploiting Depth Discontinuities for Vision-based Fingerspelling Recognition. In: IEEE Workshop on Real-Time Vision for Human-Computer Interaction (2004)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Park, J., Kim, C., Yi, J., Turk, M. (2005). Efficient Depth Edge Detection Using Structured Light. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_94

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  • DOI: https://doi.org/10.1007/11595755_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30750-1

  • Online ISBN: 978-3-540-32284-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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