IEEE Transactions on Image Processing · 2008 · 191 citations · 31 references
EngineeringMechatronics EngineeringComputer VisionDigital ImagingMachine Vision3D Imaging3D ReconstructionScene Reconstruction3D Image AcquisitionColor PatternsDynamic Scene ReconstructionFast Image AcquisitionPattern ProjectionReal-time Image AcquisitionScene Reconstruction From ImagesStructured Light
Structured light vision systems accurately measure 3‑D surfaces, but are limited to stationary objects because they require many images to recover a single 3‑D scene. The paper proposes a real‑time, single‑image 3‑D acquisition method using a specially coded vision system. The method employs a computer‑controlled color projector to display a uniquely color‑encoded matrix generated by a special code sequence and state transitions, enabling local indexing of light grids for single‑image 3‑D reconstruction. Experiments demonstrate the efficiency of the proposed single‑image 3‑D acquisition approach.
Structured light vision systems have been successfully used for accurate measurement of 3-D surfaces in computer vision. However, their applications are mainly limited to scanning stationary objects so far since tens of images have to be captured for recovering one 3-D scene. This paper presents an idea for real-time acquisition of 3-D surface data by a specially coded vision system. To achieve 3-D measurement for a dynamic scene, the data acquisition must be performed with only a single image. A principle of uniquely color-encoded pattern projection is proposed to design a color matrix for improving the reconstruction efficiency. The matrix is produced by a special code sequence and a number of state transitions. A color projector is controlled by a computer to generate the desired color patterns in the scene. The unique indexing of the light codes is crucial here for color projection since it is essential that each light grid be uniquely identified by incorporating local neighborhoods so that 3-D reconstruction can be performed with only local analysis of a single image. A scheme is presented to describe such a vision processing method for fast 3-D data acquisition. Practical experimental performance is provided to analyze the efficiency of the proposed methods.
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