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17 March 2008 Near real-time extraction of planar features from 3D flash-ladar video frames
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This paper describes a novel method used to extract planar surfaces from a stream of 3D images in near real-time. The method currently operates on 3D images acquired from a MESA SwissRanger SR-3000 infrared time of flight camera, which operates in a manner similar to flash-ladar sensors; the camera provides the user with range and intensity value for each pixel in the 176 by 144 image frame. After application of the camera calibration the range measurement associated with each pixel can be converted to a Cartesian coordinate. First, the proposed method splits the focal image plane into sub-images or sub-windows. The method then operates in the 3D parameter space to find an estimate of the planar equation best describing the point cloud associated with the window pixels and to compute a metric that defines how well the sub-window points fit to the planar estimate. The best fit sub-window is then used as an initialization to one of two investigated methods: a parameter based search technique and cluster validation using histogram thresholding to extract the entire plane from the 3D image frame. Once a plane is extracted, a feature vector describing that plane along with their describing statistics can be generated. These feature vectors can then be used to enable feature-based navigation. The paper will fully describe the feature extraction method and will provide application results of this method to extract features from indoor 3D video data obtained with the MESA SwissRanger SR-3000. Also provided is a brief overview of the generation of feature statistics and their importance.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Don Venable and Maarten Uijt de Haag "Near real-time extraction of planar features from 3D flash-ladar video frames", Proc. SPIE 6977, Optical Pattern Recognition XIX, 69770N (17 March 2008);

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