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ABSTRACT: Symmetry and affine repetitions are common in scenes with man-made structures. In this paper we propose a technique to exploit affine repetitions in a 3D scene for reconstruction and view synthesis from a single image. Assuming three vanishing points in the image, we show how the 3D structure of multiple objects and their affine repetitions may be computed and used for synthesizing new views. The reconstructed objects may also be inserted in other scenes to create augmented images.
Computer Vision, Graphics & Image Processing, 2008. ICVGIP '08. Sixth Indian Conference on; 01/2009
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ABSTRACT: We present a classifier unifying local features based representation and subspace based learning. We also propose a novel method to merge kernel eigen spaces (KES) in feature space. Subspace methods have traditionally been used with the full appearance of the image. Recently local features based bag-of-features (BoF) representation has performed impressively on classification tasks. We use KES with BoF vectors to construct class specific subspaces and use the distance of a query vector from the database KESs as the classification criteria. The use of local features makes our approach invariant to illumination, rotation, scale, small affine transformation and partial occlusions. The system allows hierarchy by merging the KES in the feature space. The classifier performs competitively on the challenging Caltech-101 dataset under normal and simulated occlusion conditions. We show hierarchy on a dataset of videos collected over the internet.
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
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ABSTRACT: This paper addresses the problem of invariant-based recognition of
quadric configurations from a single image. These configurations consist
of a pair of rigidly connected translationally repeated quadric
surfaces. This problem is approached via a reconstruction framework. A
new mathematical framework, using relative affine structure, on the
lines of Luong and Vieville (1996), has been proposed. Using this
mathematical framework, translationally repeated objects have been
projectively reconstructed, from a single image, with four image point
correspondences of the distinguished points on the object and its
translate. This has been used to obtain a reconstruction of a pair of
translationally repeated quadrics. We have proposed joint projective
invariants of a pair of proper quadrics. For the purpose of recognition
of quadric configurations, we compute these invariants for the pair of
reconstructed quadrics. Experimental results on synthetic and real
images, establish the discriminatory power and stability of the proposed
invariant-based recognition strategy. As a specific example, we have
applied this technique for discriminating images of monuments which are
characterized by translationally repeated domes modeled as
quadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence 07/2001; · 4.91 Impact Factor
