Ricardo Fabbri
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I currently work with computer vision using multiple images of the same scene (as acquired by a camera in different positions, systems of multiple cameras, or video). This is useful for automating recognition, location, and measurement of 3D objects from images, 3D photography, etc. I am concerned with devising robust, precise and automatic methods for tackling problems in this area. In order to meet such requirements, I explore the use of grouped primitives such as curves and their differential geometry as the basis for the methods. I believe this is a much more powerful approach to solve multiview problems than the traditional one which relies on point primitives. I have been recently working on fusing a number of cues for 3D reconstruction. The end-goal is a system based on a hand-held video sequence, without need for calibration or textured regions, being able to identify not only the 3D structure of objects, but also the camera position, the reflectance properties, and lighting conditions as well


demonstration video
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as author at  23rd IEEE Conference on Computer Vision and Pattern Recognition 2010 - San Francisco,
together with: Yasutaka Furukawa, Dirk Schnieders, Carl Olsson, Qingxiong Yang, Xiaoyan Hu, Yekeun Jeong, Tai-Pang Wu, Yuping Lin, Richard Newcombe, Tali Bahsa, Vivek Pradeep, Junghyun Kwon, Shubao Liu, Margarita Chli, Peter Lindstrom, Branislav Micusik, Michael Bleyer, Guillaume Batog, Arjun Jain, Michela Farenzena, Jun Sato,