A Variational Framework for Structure from Motion in Omnidirectional Image Sequences
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Vision sensor networks and video cameras find widespread usage in several applications that rely on effective representation of scenes or analysis of 3D information. These systems usually acquire multiple images of the same 3D scene from different viewpoin ...
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In this paper, we analyze our graph-based approach for 2D and 3D object duplicate detection in still images. A graph model is used to represent the 3D spatial information of the object based on the features extracted from training images so that an explici ...
2010
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Dense three-dimensional reconstruction of a scene from images is a challenging task. Usually, it is achieved by finding correspondences in successive images and computing the distance by means of epipolar geometry. In this paper, we propose a variational f ...
2010
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We address the problem of depth and ego-motion estimation from omnidirectional images. We propose a correspondence-free structure from motion problem for images mapped on the 2-sphere. A novel graph-based variational framework is proposed for depth estimat ...
Springer Verlag2011
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Dense three-dimensional reconstruction of a scene from images is a very challenging task. In the structure from motion approach one of the key points is to compute depth maps which contain the distance of objects in the scene to a moving camera. Usually, t ...
