Realtime structured light patterns coding with subperfect submaps Coded structured light is a technique that allows the 3D reconstruction of poorly or nontextured scene areas. The codes, uniquely associated with visual primitives of the projected pattern, allow to solve the correspondence problem using local information only with robustness against pertubations like high curvatures, occlusions, out of field of view, outoffocus. Realtime 3D reconstruction is possible with pseudorandom arrays, where the encoding is done in a single pattern using spatial neighbourhood. Ensuring a higher Hamming distance between all the used codewords, will allow to correct more mislabeled primitives and thus ensure patterns globally more robust. 1  Up to now, the proposed coding schemes ensured the Hamming distance between all the primitives of the pattern which was generated offline, beforehand, producing Perfect SubMaps (PSM). But knowing the epipolar geometry of the projectorcamera system, one can ensure the Hamming distance only between primitives that will project along nearby epipolar lines, because these only can produce correspondence ambiguity during the decoding process. As for such a new coding scheme, the Hamming distance have to be checked only in subsets of the pattern primitives, the patterns are globally far less constrained and therefore can be generated at a video framerate. We call such a new pattern coding as SubPerfect SubMaps (SPSM).

A Structured Light Encoding Method for Marray Technique In this paper, we have designed a structured light encoding algorithm based on the fillandtestasyougoalong method. The algorithm achieves significant improvement for the structured light encoding technology, which could encode a lager resolution pattern with a certain number of symbols for encoding. It is significant to improve the accuracy of 3D recognition using the structured light (SL) technology, and reduce the complexity of the structured light algorithm, which is wildly used in 3D reconstruction, tactile sensor based on vision, grasping and so on. In the comparative experiment, we obtain nearly twice the size of the pattern encoded by the proposed encoding algorithm.