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3D object model recovery from 2D images using structured light

Philippe Lavoie, Dan Ionescu, Emil M. Petriu

发表年份
2004
引用次数
54

摘要

Three-dimensional (3-D) object models are currently used in CAD/CAM, robotics, remote sensing, etc. The models (images) can be either directly acquired by using special devices such as range finders, CTR scanners, etc., or they can be recovered from a series of two-dimensional (2-D) images of the object. In this paper, the authors propose a method for determining a set of reference pixels in two simultaneous views of the same object, using two cameras, by projecting a pseudorandom encoded grid on the object. The grid nodes and their encoding values are extracted from 2-D images by applying first a smoothing and then a watershed algorithm. The pseudorandom information encoded in the grid nodes is used to match corresponding sets of points of the two 2-D images. The set of matched points are further used to calculate the disparity of each point of the object surface. Experimental examples illustrate the performance of this simple and elegant technique.

关键词

Computer visionArtificial intelligenceObject (grammar)Computer scienceGridPixelSmoothingSet (abstract data type)Object detectionObject model

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