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Decision Trees For Geometric Models
, 1993
"... A fundamental problem in modelbased computer vision is that of identifying which of a given set of geometric models is present in an image. Considering a "probe" to be an oracle that tells us whether or not a model is present at a given point, we study the problem of computing efficien ..."
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Cited by 36 (4 self)
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A fundamental problem in modelbased computer vision is that of identifying which of a given set of geometric models is present in an image. Considering a "probe" to be an oracle that tells us whether or not a model is present at a given point, we study the problem of computing efficient strategies ("decision trees") for probing an image, with the goal to minimize the number of probes necessary (in the worst case) to determine which single model is present. We show that a dlg ke height binary decision tree always exists for k polygonal models (in fixed position), provided (1) they are nondegenerate (do not share boundaries) and (2) they share a common point of intersection. Further, we give an efficient algorithm for constructing such decision tress when the models are given as a set of polygons in the plane. We show that constructing a minimum height tree is NPcomplete if either of the two assumptions is omitted. We provide an efficient greedy heuristic strategy and show ...
Point Probe Decision Trees for Geometric Concept Classes
, 1993
"... A fundamental problem in modelbased computer vision is that of identifying to which of a given set of concept classes of geometric models an observed model belongs. Considering a "probe" to be an oracle that tells whether or not the observed model is present at a given point in an image, ..."
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Cited by 7 (5 self)
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A fundamental problem in modelbased computer vision is that of identifying to which of a given set of concept classes of geometric models an observed model belongs. Considering a "probe" to be an oracle that tells whether or not the observed model is present at a given point in an image, we study the problem of computing efficient strategies ("decision trees") for probing an image, with the goal to minimize the number of probes necessary (in the worst case) to determine in which class the observed model belongs. We prove a hardness result and give strategies that obtain decision trees whose height is within a log factor of optimal. These results grew out of discussions that began in a series of workshops on Geometric Probing in Computer Vision, sponsored by the Center for Night Vision and ElectroOptics, Fort Belvoir, Virginia, and monitored by the U.S. Army Research Office. The views, opinions, and/or findings contained in this report are those of the authors and should not be con...
Geometric Methods for Optical Character Recognition
, 1997
"... of the Dissertation Geometric Methods for Optical Character Recognition by George N. Sazaklis Doctor of Philosophy in Computer Science State University of New York at Stony Brook Advisor: Joseph S. B. Mitchell 1997 Abstract Optical Character Recognition (OCR) is an important problem havin ..."
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of the Dissertation Geometric Methods for Optical Character Recognition by George N. Sazaklis Doctor of Philosophy in Computer Science State University of New York at Stony Brook Advisor: Joseph S. B. Mitchell 1997 Abstract Optical Character Recognition (OCR) is an important problem having both theoretical and practical interest. In this dissertation, we present solutions to three problems within the area of OCR. A difficulty encountered by many OCR systems is confusions between similar shapes, when flexible matching is employed as a primary recognition mechanism. Our solution, constrained matching as a second stage classification technique, can discriminate between similar shapes, using shape geometric attributes; thus the system is enabled to reach a final decision on the character identity. Another important problem in OCR is the fast and reliable fixedfont recognition. We present a hierarchical classification technique that utilizes the concept of geometric probe tree...