Scene-adapted structured light

In order to overcome several limitations of structured light 3D acquisition methods, the colors, intensities, and shapes of the projected patterns are adapted to the scene. Based on a crude estimate of the scene geometry and reflectance characteristics, the local intensity ranges in the projected patterns are adapted, in order to avoid over- and under-exposure in the image. This avoids the infamous specularity problems and generally increases accuracy. The estimated geometry also helps to limit the effect of aliasing caused by the sampling of foreshortened patterns. Furthermore, the approach also accounts for the adverse effects that small motions during scanning would normally have. Moreover, the approach yields a confidence measure at every pixel of the range image. Last but not least, the scanner consists of consumer products only, and therefore is cheap.

[1]  Shree K. Nayar,et al.  Programmable imaging using a digital micromirror array , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[2]  Guy Godin,et al.  Recursive model optimization using ICP and free moving 3D data acquisition , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[3]  Vladimir Kolmogorov,et al.  What energy functions can be minimized via graph cuts? , 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Joaquim Salvi,et al.  Recent progress in coded structured light as a technique to solve the correspondence problem: a survey , 1998, Pattern Recognit..

[5]  Richard Szeliski,et al.  High dynamic range video , 2003, ACM Trans. Graph..

[6]  Sang Wook Lee,et al.  High-Contrast Color-Stripe Pattern for Rapid Structured-Light Range Imaging , 2004, ECCV.

[7]  Franc¸ois Blais,et al.  Review of 20 years of range sensor development , 2003, IS&T/SPIE Electronic Imaging.

[8]  Szymon Rusinkiewicz,et al.  Stripe boundary codes for real-time structured-light range scanning of moving objects , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[9]  Nahum Kiryati,et al.  Toward optimal structured light patterns , 1999, Image Vis. Comput..

[10]  Joseph Shamir,et al.  Range Imaging With Adaptive Color Structured Light , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Luc Van Gool,et al.  Real-time range scanning of deformable surfaces by adaptively coded structured light , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[12]  Richard Szeliski,et al.  High-accuracy stereo depth maps using structured light , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[13]  Munther A Gdeisat,et al.  Robust, fast, and effective two-dimensional automatic phase unwrapping algorithm based on image decomposition. , 2002, Applied optics.

[14]  Shree K. Nayar,et al.  Programmable imaging using a digital micromirror array , 2004, CVPR 2004.

[15]  Robert L. Stevenson,et al.  Dynamic range improvement through multiple exposures , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[16]  Shree K. Nayar,et al.  Making one object look like another: controlling appearance using a projector-camera system , 2004, CVPR 2004.