Maximum a posteriori-based depth sensing with a single-shot maze pattern.

This study addressed the general problem of correspondence retrieval for single-shot depth sensing where the coded features cannot be detected perfectly. The traditional correspondence retrieval technique can be regarded as maximum likelihood estimation with a uniform distribution prior assumption, which may lead to mismatches for two types of insignificant features: 1) incomplete features that cannot be detected completely because of edges, tiny objects, and many depth variations, etc.; and 2) distorted features disturbed by environmental noise. To overcome the drawback of the uniform distribution assumption, we propose a maximum a posteriori estimation-based correspondence retrieval method that uses the significant features as priors to estimate the weak or missing features. We also propose a novel monochromatic maze-like pattern, which is more robust to ambient illumination and the colors in scenes than the traditional patterns. Our experimental results demonstrate that the proposed system performs better than the popular RGB-D cameras and traditional single-shot techniques in terms of accuracy and robustness, especially with challenging scenes.

Single-Shot Dense Depth Sensing with Color Sequence Coded Fringe Pattern.

A single-shot structured light method is widely used to acquire dense and accurate depth maps for dynamic scenes. In this paper, we propose a color sequence coded fringe depth sensing method. To overcome the phase unwrapping problem encountered in phase-based methods, the color-coded sequence information is embedded into the phase information. We adopt the color-encoded De Bruijn sequence to denote the period of the phase information and assign the sequence into two channels of the pattern, while the third channel is used to code the phase information. Benefiting from this coding strategy, the phase information distributed in multiple channels can improve the quality of the phase intensity by channel overlay, which results in precise phase estimation. Meanwhile, the wrapped phase period assists the sequence decoding to obtain a precise period order. To evaluate the performance of the proposed method, an experimental platform is established. Quantitative and qualitative experiments demonstrate that the proposed method generates a higher precision depth, as compared to a Kinect and larger resolution ToF (Time of Flight) camera.

One-shot depth acquisition with a random binary pattern.

In this paper, we propose a new spatial encoding method that integrates the random binary pattern and the improved phase-difference-matching method to acquire a dense and precise depth map. The adopted binary pattern can simplify pattern projecting devices compared with the patterns that use color. The density of speckles in the pattern is periodic and the positions of them are random. Based on these two properties, we propose an improved phase-difference corresponding method, which is divided into two steps: the coarse matching step to estimate the approximate coordinates of pixels in the pattern via analyzing the phase values of the image, and the fine matching step to compensate errors of the coarse matching results and to achieve subpixel accuracy. This matching method does not require an extra optimization method with high computational complexity. In the experiment, we show the effectiveness of the proposed method. We also evaluate this method in actual experiments. The results show that this method has advantages over the time-of-flight camera and Kinect, particularly in terms of precision.