Author
A. Acharyya
Bio: A. Acharyya is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Incremental heuristic search & Pattern recognition (psychology). The author has an hindex of 1, co-authored 1 publications receiving 14 citations.
Papers
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TL;DR: A new heuristic search based approach for recognition of partially obscured planar shapes using an admissible heuristic function which is not dependent upon the features actually used for representing the shapes.
14 citations
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TL;DR: This method is able to obtain reliable stroke correspondence and enable structural interpretation and some structural post-processing operations are applied to improve the stroke correspondence.
107 citations
TL;DR: Experimental results presented here highlight the effectiveness of this method for approximating object boundaries of polygonal as well as curved shapes present in the images of complex multi-object scenes even in the presence of noise.
19 citations
01 Apr 1998
TL;DR: Results are presented which demonstrate that an iterative, coarse-to-fine sum-squared-error method that uses information from hypothesized occlusion events to perform run-time modification of scene- to-template similarity measures is reasonably robust over a large database of color test scenes containing objects at a variety of scales and tolerates minor 3D object rotations and global illumination variations.
Abstract: In this paper, we discuss an appearance-matching approach to the difficult problem of interpreting color scenes containing occluded objects. We have explored the use of an iterative, coarse-to-fine sum-squared-error method that uses information from hypothesized occlusion events to perform run-time modification of scene-to-template similarity measures. These adjustments are performed by using a binary mask to adaptively exclude regions of the template image from the squared-error computation. At each iteration higher resolution scene data as well as information derived from the occluding interactions between multiple object hypotheses are used to adjust these masks. We present results which demonstrate that such a technique is reasonably robust over a large database of color test scenes containing objects at a variety of scales, and tolerates minor 3D object rotations and global illumination variations.
17 citations
TL;DR: In this paper, the phase-only filter, the inverse filter and the minimum variance -minimum average correlation energy filter are considered for pattern recognition of occluded objects, and numerical and optical results of the recognition are presented.
16 citations
TL;DR: A bibliography of over 1600 references related to computer vision and image analysis, arranged by subject matter is presented, covering topics including architectures; computational techniques; feature detection, segmentation, and imageAnalysis.
Abstract: This paper presents a bibliography of over 1600 references related to computer vision and image analysis, arranged by subject matter. The topics covered include architectures; computational techniques; feature detection, segmentation, and image analysis; matching, stereo, and time-varying imagery; shape and pattern; color and texture; and three-dimensional scene analysis. A few references are also given on related topics, such as computational geometry, computer graphics, image input/output and coding, image processing, optical processing, visual perception, neural nets, pattern recognition, and artificial intelligence.
16 citations