On the de Bruijn Torus problem
Journal of Combinatorial Theory Series A
Structured Light Using Pseudorandom Codes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A robust-coded pattern projection for dynamic 3D scene measurement
Pattern Recognition Letters
Real-Time Range Acquisition by Adaptive Structured Light
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Calibration of vision systems based on pseudo-random patterns
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
IEEE Transactions on Information Theory
Aperiodic and semi-periodic perfect maps
IEEE Transactions on Information Theory
Constructions for perfect maps and pseudorandom arrays
IEEE Transactions on Information Theory - Part 1
Vision Processing for Realtime 3-D Data Acquisition Based on Coded Structured Light
IEEE Transactions on Image Processing
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Coded structured light is a technique that allows the 3D reconstruction of poorly or non-textured scene areas. With the codes uniquely associated with visual primitives of the projected pattern, the correspondence problem is quickly solved by means of local information only, with robustness against disturbances like high surface curvatures, partial occlusions, out-of-field of view or out-of-focus. Real-time 3D reconstruction with one shot is possible with pseudo-random arrays, where the encoding is done in a single pattern using spatial neighbourhood. To correct more mismatched visual primitives and to get patterns globally more robust, a higher Hamming distance between all the used codewords should be suited. Recent works in the structured light field have shown a growing interest for adaptive patterns. These can account for geometrical or spectral specificities of the scene to provide better features matching and reconstructions. Up till today, such patterns cannot benefit from the robustness offered by spatial neighbourhood coding with a minimal Hamming distance constraint, because the existing algorithms for such a class of coding are designed with an offline coding only. In this article, we show that due to two new contributions, a mixed exploration/exploitation search behaviour and a O(n 2) to ~O(n) complexity reduction using the epipolar constraint, the real-time coding of patterns having similar properties than those coded offline can be achieved. This allows to design a complete closed-loop processing pipeline for adaptive patterns.