TR2012-077

Motion-Aware Structured Light Using Spatio-Temporal Decodable Patterns


    •  Taguchi, Y., Agrawal, A., Tuzel, O., "Motion-Aware Structured Light Using Spatio-Temporal Decodable Patterns", European Conference on Computer Vision (ECCV), October 2012.
      BibTeX TR2012-077 PDF
      • @inproceedings{Taguchi2012oct1,
      • author = {Taguchi, Y. and Agrawal, A. and Tuzel, O.},
      • title = {Motion-Aware Structured Light Using Spatio-Temporal Decodable Patterns},
      • booktitle = {European Conference on Computer Vision (ECCV)},
      • year = 2012,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2012-077}
      • }
  • Research Area:

    Computer Vision

Abstract:

Single-shot structured light methods allow 3D reconstruction of dynamic scenes. However, such methods lose spatial resolution and perform poorly around depth discontinuities. Previous single-shot methods project the same pattern repeatedly; thereby spatial resolution is reduced even if the scene is static or has slowly moving parts. We present a structured light system using a sequence of shifted stripe patterns that is decodable both spatially and temporally. By default, our method allows single-shot 3D reconstruction with any of our projected patterns by using spatial windows. Moreover, the sequence is designed so as to progressively improve the reconstruction quality around depth discontinuities by using temporal windows. Our method enables motion-aware reconstruction for each pixel: The best spatio-temporal window is automatically selected depending on the scene structure, motion, and the number of available images. This significantly reduces the number of pixels around discontinuities where depth cannot be recovered in traditional approaches. Our decoding scheme extends the adaptive window matching commonly used in stereo by incorporating temporal windows with 1D spatial windows. We demonstrate the advantages of our approach for a variety of scenarios including thin structures, dynamic scenes, and scenes containing both static and dynamic regions.

 

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