Structured light using pseudorandom codes

Morano, R.A.; Ozturk, Cengizhan; Conn, Richard W.; Dubin, Stephen; Zietz, S; Nissano, J.

doi:10.1109/34.667888

Cited by 186 publications

(101 citation statements)

References 10 publications

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“…• Morano: pattern consisting of colour dots encoded with an M -array of 45 × 45 elements and three colours [45]. The headings are: author's name of the technique; standard deviation of the reconstructing error; average number of 3D points; % of pixels from images that have been reconstructed in average; number of projected patterns.…”

Section: Resultsmentioning

confidence: 99%

“…One of the most interesting techniques from this group was given by Morano et al [45]. The authors proposed an algorithm for constructing an M -array, ÿxing the length of the alphabet, the window property size, the dimensions of the array and the Hamming distance between every window.…”

Section: Strategies Based On M-arraysmentioning

confidence: 99%

“…Furthermore, techniques based on both axis codiÿcation, i.e. the grid by Salvi et al [34] and the array of dots by Morano et al [45], are more robust against discontinuities as redundancy in the coding strategy permits extension of decoded regions to contiguous non-decoded regions. Finally, the direct coded pattern presented by Sato [52] has obtained very accurate results (also locating the stripes with sub-pixel accuracy) and robustness against colourful surfaces.…”

Section: Qualitative Evaluationmentioning

confidence: 99%

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Pattern codification strategies in structured light systems

Salví

Pagès

Batlle

2004

Pattern Recognition

996

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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Section: Resultsmentioning

confidence: 99%

Section: Strategies Based On M-arraysmentioning

confidence: 99%

Section: Qualitative Evaluationmentioning

confidence: 99%

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Pattern codification strategies in structured light systems

Salví

Pagès

Batlle

2004

Pattern Recognition

996

491

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“…This type of arrays has also the window property, but not all the possible windows are included. Morano et al [9] proposed a brute force algorithm for generating perfect submaps. For example, in order to generate a 6 × 6 M-array with window property 3 × 3 using an alphabet of 3 elements the procedure is as follows: firstly, a subarray of 3 × 3 is randomly chosen and it is placed in the north-west vertex of the M-array that is being built as shown in Fig.…”

Section: A Formal Definitionmentioning

confidence: 99%

“…In most cases, patterns containing an array of spots are used like in [8], [9]. Every element of the alphabet is assigned to a grey level or a colour.…”

Section: B Pattern Designmentioning

confidence: 99%

An approach to visual servoing based on coded light

Pagès

Collewet²,

Chaumette³

et al.

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

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Abstract-Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of non-textured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance.

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Image Analysis and Computer Vision: 1998

Rosenfeld

1999

Computer Vision and Image Understanding

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This paper presents a bibliography of over 2250 references related to computer vision and image analysis, arranged by subject matter. The topics covered include computational techniques; feature detection and segmentation; image and scene analysis; two-dimensional shape; pattern; color and texture; matching and stereo; three-dimensional recovery and analysis; three-dimensional shape; and motion. A few references are also given on related topics, including geometry and graphics, compression and processing, sensors and optics, visual perception, neural networks, artificial intelligence and pattern recognition, as well as on applications.

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Structured light using pseudorandom codes

Cited by 186 publications

References 10 publications

Pattern codification strategies in structured light systems

Pattern codification strategies in structured light systems

An approach to visual servoing based on coded light

Image Analysis and Computer Vision: 1998

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