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Results 11 - 20
of
16,619
to Object Recognition.
, 1997
"... Selecting the toroidal self-organizing feature maps (TSOFM) best organized to object recognition ..."
Abstract
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Selecting the toroidal self-organizing feature maps (TSOFM) best organized to object recognition
Context-Based Vision System for Place and Object Recognition
, 2003
"... While navigating in an environment, a vision system has' to be able to recognize where it is' and what the main objects' in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is' to identify familiar locations' (e ..."
Abstract
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Cited by 317 (9 self)
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While navigating in an environment, a vision system has' to be able to recognize where it is' and what the main objects' in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is' to identify familiar locations
Object recognition
"... Object recognition is concerned with determining the identity of an object being observed in the image from a set of known labels. Oftentimes, it is assumed that the object being observed has been detected or there is a single object in the image. ..."
Abstract
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Object recognition is concerned with determining the identity of an object being observed in the image from a set of known labels. Oftentimes, it is assumed that the object being observed has been detected or there is a single object in the image.
Object recognition with features inspired by visual cortex
- CVPR’05 -Volume
, 2005
"... We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edgedetectors over neighboring positions and multiple orientations. Our system’s architecture is motivated by a quantitative model of v ..."
Abstract
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Cited by 291 (17 self)
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We introduce a novel set of features for robust object recognition. Each element of this set is a complex feature obtained by combining position- and scale-tolerant edgedetectors over neighboring positions and multiple orientations. Our system’s architecture is motivated by a quantitative model
OBJECT RECOGNITION
"... Object recognition is a subproblem of the more general problem of perception, and can be defined as follows. Given a scene consisting of one or more objects, can we identify and localize those objects that are sufficiently visible to the sensory system? It is generally assumed that a description of ..."
Abstract
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Object recognition is a subproblem of the more general problem of perception, and can be defined as follows. Given a scene consisting of one or more objects, can we identify and localize those objects that are sufficiently visible to the sensory system? It is generally assumed that a description
Generic Object Recognition with Boosting
- IEEE Trans. PAMI
, 2006
"... This paper presents a powerful framework for generic object recognition. Boosting is used as an underlying learning technique. For the first time a combination of various weak classifiers of different types of descriptors is used, which slightly increases the classification result but dramatically i ..."
Abstract
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Cited by 144 (6 self)
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This paper presents a powerful framework for generic object recognition. Boosting is used as an underlying learning technique. For the first time a combination of various weak classifiers of different types of descriptors is used, which slightly increases the classification result but dramatically
Color Based Object Recognition
- Pattern Recognition
, 1997
"... This paper is organized as follows. In Section 2, the dichromatic reflectance under "white" reflection is introduced and new photometric invariant color features are proposed. The performance of object recognition by histogram matching differentiated for the various color models is evaluat ..."
Abstract
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Cited by 149 (26 self)
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This paper is organized as follows. In Section 2, the dichromatic reflectance under "white" reflection is introduced and new photometric invariant color features are proposed. The performance of object recognition by histogram matching differentiated for the various color models
Support vector machines for 3-D object recognition
- PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1998
"... Support Vector Machines (SVMs) have been recently proposed as a new technique for pattern recognition. Intuitively, given a set of points which belong to either of two classes, a linear SVM finds the hyperplane leaving the largest possible fraction of points of the same class on the same side, while ..."
Abstract
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Cited by 252 (14 self)
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, while maximizing the distance of either class from the hyperplane. The hyperplane is determined by a subset of the points of the two classes, named support vectors, and has a number of interesting theoretical properties. In this paper, we use linear SVMs for 3D object recognition. We illustrate
What is the Best Multi-Stage Architecture for Object Recognition?
"... In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer. Most systems use only one stage of feature extraction in which the filters are hard-wired, or two stages where the filter ..."
Abstract
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Cited by 252 (22 self)
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In many recent object recognition systems, feature extraction stages are generally composed of a filter bank, a non-linear transformation, and some sort of feature pooling layer. Most systems use only one stage of feature extraction in which the filters are hard-wired, or two stages where
Object Recognition
- Wiley Encyclopedia of Electrical and Electronics Engineering
, 2000
"... e 2-D image. Since humans can perform this task effortlessly, it was believed then that designing a computer-based system for accomplishing the same would be easy. However, forty years later today this problem remains largely unsolved. In contrast, much progress has been made in recognizing 2-D obje ..."
Abstract
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Cited by 2 (1 self)
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objects in single 2-D images and in recognizing 3-D objects in range maps. Although not as impressive, considerable progress has also been made in the recognition of 2-D or 3-D objects using multiple 2-D images, as in binocular or multiple-camera stereo. The earliest successful system for the recognition
Results 11 - 20
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