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Results 11 - 20
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1,850
Pedestrian Detection by Modeling Local Convex Shape Features
"... This paper presents a pedestrian model built collectively on a group of strong local convex shape descriptors. The pedestrian model captures the most important features of a pedestrian: head, body contour, arms, legs and crotch, and is robust to variances in appearances and partial occlusions. For a ..."
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Cited by 1 (0 self)
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This paper presents a pedestrian model built collectively on a group of strong local convex shape descriptors. The pedestrian model captures the most important features of a pedestrian: head, body contour, arms, legs and crotch, and is robust to variances in appearances and partial occlusions
A Novel Approach for Area Computation of Convex Shapes
"... Abstract—Shape analysis is widely applied in image registration, segmentation, classification and various other computer vision applications like pattern recognition, medical image diagnostics, integral geometry etc. Area measure plays a very important role in image classification based on size of t ..."
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of the image. The area of an object is a convenient measure of the objects’ overall size and is a widely used simple scalar descriptor. This paper describes a new scale invariant area computation algorithm for convex shapes with constant time complexity which can also be used for computation of various scalar
Matching Convex Shapes with Respect to the Symmetric Difference
, 1998
"... This paper deals with questions from convex geometry related to shape matching. In particular, we consider the problem of moving one convex figure over another, minimizing the area of their symmetric difference. We show that if we just let the two centers of gravity coincide, the resulting symmetric ..."
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Cited by 39 (6 self)
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This paper deals with questions from convex geometry related to shape matching. In particular, we consider the problem of moving one convex figure over another, minimizing the area of their symmetric difference. We show that if we just let the two centers of gravity coincide, the resulting
New Approximation Algorithms for Minimum Enclosing Convex Shapes
"... Given n points in a d dimensional Euclidean space, the Minimum Enclosing Ball (MEB) problem is to find the ball with the smallest radius which contains all n points. We give two approximation algorithms for producing an enclosing ball whose radius is at most ɛ away from the optimum. The first requir ..."
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Cited by 3 (0 self)
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the Minimum Enclosing Convex Polytope (MECP) is a related problem wherein a convex polytope of a fixed shape is given and the aim is to find the smallest magnification of the polytope which encloses the given points. For this problem we present O(mndL/ɛ) and O ∗ (mndQ/ɛ) approximation algorithms, where m
Efficient approximation algorithms for minimum enclosing convex shapes
, 2009
"... We address the problem of Minimum Enclosing Ball (MEB) and its generalization to Minimum Enclosing Convex Polytope (MECP). Given n points in a d dimensional Euclidean space, we give a O(nd / √ ɛ) algorithm for producing an enclosing ball whose radius is at most ɛ away from the optimum. In the case ..."
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Cited by 2 (0 self)
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We address the problem of Minimum Enclosing Ball (MEB) and its generalization to Minimum Enclosing Convex Polytope (MECP). Given n points in a d dimensional Euclidean space, we give a O(nd / √ ɛ) algorithm for producing an enclosing ball whose radius is at most ɛ away from the optimum. In the case
DISCRIMINATION OF CLASSES WITH CORRELATED ATTRIBUTES AND NON CONVEX SHAPE
"... Abstract: We use the classification method Fuzzy Pattern Matching (FPM) to realize the industrial and medical diagnosis. FPM is decentralized, i.e., its global decision is based on the selection of one of the intermediate decisions. Each intermediate decision is based on one attribute. Thus, FPM doe ..."
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does not take into account the correlation between attributes. Additionally, FPM does not respect the shape of classes if this shape is non convex. These drawbacks make FPM unusable for many real world applications. In this paper, we propose to improve FPM to solve these drawbacks. Three examples
Similarity and Symmetry Measures for Convex Shapes Using Minkowski Addition
, 1997
"... This paper is devoted to similarity and symmetry measures for convex shapes whose definition is based on Minkowski addition and the Brunn-Minkowski inequality. This means in particular that these measures are region-based, in contrast to most of the literature, where one considers contour-based meas ..."
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Cited by 16 (0 self)
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This paper is devoted to similarity and symmetry measures for convex shapes whose definition is based on Minkowski addition and the Brunn-Minkowski inequality. This means in particular that these measures are region-based, in contrast to most of the literature, where one considers contour
From Few to many: Illumination cone models for face recognition under variable lighting and pose
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2001
"... We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination conditions, is a convex cone in the space of images. Using a smal ..."
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Cited by 754 (12 self)
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We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination conditions, is a convex cone in the space of images. Using a
Privileged Coding of Convex Shapes in Human Object-Selective Cortex
, 2008
"... You might find this additional information useful... Supplemental material for this article can be found at: ..."
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Cited by 4 (0 self)
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You might find this additional information useful... Supplemental material for this article can be found at:
Scale-Aware Object Tracking with Convex Shape Constraints on RGB-D Images
"... Abstract. Convex relaxation techniques have become a popular approach to a variety of image segmentation problems as they allow to compute solutions independent of the initialization. In this paper, we propose a novel technique for the segmentation of RGB-D images using convex function optimization. ..."
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Cited by 1 (1 self)
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Abstract. Convex relaxation techniques have become a popular approach to a variety of image segmentation problems as they allow to compute solutions independent of the initialization. In this paper, we propose a novel technique for the segmentation of RGB-D images using convex function optimization
Results 11 - 20
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1,850
