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30 May 2003 Digital three-dimensional object reconstruction and correlation based on integral imaging
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Integral images contain multiple views of a scene obtained from slightly different points of view. They therefore include three-dimensional (3D) information - including depth - about the scenes they represent. In this paper, we propose to use this depth information contained in integral images in order to recognize 3D objects. The integral images are first used to estimate the longitudinal distances of the objects composing the 3D scene. Using this information, a 3D model of the scene is reconstructed in the computer. These models are then used to compute digital 3D correlations between various scenes and objects. For a better discrimination we use a nonlinear 3D correlation. We present experimental results for digital 3D reconstruction of real 3D scenes containing several objects at various distances. With these experimental data, we demonstrate the recognition and 3D localization of objects through nonlinear correlation. We investigate the effect of the nonlinearity strength in the correlation. We finally present experiments to show that the three-dimensional correlation is more discriminant than the two-dimensional correlation.
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Yann Frauel and Bahram Javidi "Digital three-dimensional object reconstruction and correlation based on integral imaging", Proc. SPIE 5006, Stereoscopic Displays and Virtual Reality Systems X, (30 May 2003);

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