3-D data acquisition by Rainbow Range Finder

Tajima, Johji; Iwakawa, Mayumi

doi:10.1109/icpr.1990.118121

Cited by 58 publications

(48 citation statements)

References 5 publications

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“…With the patterns which use many colors and all pixels in the image [9], the correspondence can be uniquely determined, in the case of zero noise. On the other hand, sparse grid pattens [2,8,10] are inherently ambiguous and require elaborate optimization for decoding, but the localization of each pattern is robust to small perturbation of observed intensity.…”

Section: Related Workmentioning

confidence: 99%

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Hamming Color Code for Dense and Robust One-shot 3D Scanning

Yamazaki

Nukada

Mochimaru

2011

Procedings of the British Machine Vision Conference 2011

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We propose a novel color code, Hamming color code, designed for rapid 3D shape acquisition using structured light projection. The Hamming color code has several properties which are desirable for practical 3D acquisition as follows. First, the Hamming distance of adjacent colors is always 1, which makes the color detection robust to color blending due to defocusing, subsurface scattering, or chromatic aberration. Second, the substrings of a certain length is guaranteed to be unique. In other words, the Hamming code can be viewed as a subset of de Bruijn sequence. Third, a one-dimensional coordinate can be encoded for each pixel, which enables dense 3D reconstruction from a single pattern projection. Thanks to the uniqueness and robustness of the substrings, the structured light can be decoded stably by dynamic programming. We have implemented parallel dynamic programming on GPU and achieved the speed-up by a factor of 630 compared to the CPU-based implementation, and accomplished video-rate 3D acquisition using commodity hardware. Several experiments have been conducted to demonstrate the stability and performance of our algorithm. Finally we discuss the limitation and future direction of this work.

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Section: Related Workmentioning

confidence: 99%

“…One of the simple patterns is a color gradient (or rainbow pattern) [9]. Robustness to the inhomogeneous surface color can be improved by using pseudo-random number sequences.…”

Section: Related Workmentioning

confidence: 99%

Hamming Color Code for Dense and Robust One-shot 3D Scanning

Yamazaki

Nukada

Mochimaru

2011

Procedings of the British Machine Vision Conference 2011

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“…However, colour is used to encode pixels instead of using grey levels. For instance, Tajima and Iwakawa [50] presented the rainbow pattern. A large set of vertical narrow slits were encoded with di erent wavelengths, so that a large sampling of the spectrum from red to blue was projected.…”

Section: Codiÿcation Based On Colourmentioning

confidence: 99%

Pattern codification strategies in structured light systems

Salví

Pagès

Batlle

2004

Pattern Recognition

997

491

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Coded structured light is considered one of the most reliable techniques for recovering the surface of objects. This technique is based on projecting a light pattern and viewing the illuminated scene from one or more points of view. Since the pattern is coded, correspondences between image points and points of the projected pattern can be easily found. The decoded points can be triangulated and 3D information is obtained. We present an overview of the existing techniques, as well as a new and deÿnitive classiÿcation of patterns for structured light sensors. We have implemented a set of representative techniques in this ÿeld and present some comparative results. The advantages and constraints of the di erent patterns are also discussed.

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“…Tajima and Iwakawa suggest a rainbow pattern [8]. A large set of vertical slits are encoded using different wavelengths such that a large sampling of the spectrum from red to blue is used.…”

Section: Direct Codificationmentioning

confidence: 99%