1 November 1992 Stochastic structure estimation by motion
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Proceedings Volume 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods; (1992) https://doi.org/10.1117/12.131624
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
A field of great interest in computer vision is depth reconstruction by motion. The final goal is the computation of the visible surface structure in a 3D scene by analyzing a sequence of digital images acquired moving a camera in the environment. This paper describes a method of depth reconstruction based on stochastic modeling of the motion, the image acquisition processes, and the 3D-2D projection. The stochastic model is based on the well-known extended Kalman filter to derive an optimized depth estimation: it integrates successive views by using a pair of optical flow equations that we have adapted to a general pin-hole camera model (linear transformation from 3D to 2D coordinates). In comparison with similar methods we developed a reconstruction system to improve the speed of the estimation process and its stability by means of a multi-scale approach and used a massive parallel MIMD machine to speed up globally the estimation process.
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Arcangelo Distante, Arcangelo Distante, Francesco P. Lovergine, Francesco P. Lovergine, Giovanni Attolico, Giovanni Attolico, Maria Teresa Chiaradia, Maria Teresa Chiaradia, Laura Caponetti, Laura Caponetti, } "Stochastic structure estimation by motion", Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131624; https://doi.org/10.1117/12.131624
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