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Good features to track

by Jianbo Shi, Carlo Tomasi , 1994
"... No feature-based vision system can work unless good features can be identified and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature se ..."
Abstract - Cited by 2050 (14 self) - Add to MetaCart
No feature-based vision system can work unless good features can be identified and tracked from frame to frame. Although tracking itself is by and large a solved problem, selecting features that can be tracked well and correspond to physical points in the world is still hard. We propose a feature

Supervised and unsupervised discretization of continuous features

by James Dougherty, Ron Kohavi, Mehran Sahami - in A. Prieditis & S. Russell, eds, Machine Learning: Proceedings of the Twelfth International Conference , 1995
"... Many supervised machine learning algorithms require a discrete feature space. In this paper, we review previous work on continuous feature discretization, identify de n-ing characteristics of the methods, and conduct an empirical evaluation of several methods. We compare binning, an unsupervised dis ..."
Abstract - Cited by 540 (11 self) - Add to MetaCart
Many supervised machine learning algorithms require a discrete feature space. In this paper, we review previous work on continuous feature discretization, identify de n-ing characteristics of the methods, and conduct an empirical evaluation of several methods. We compare binning, an unsupervised

Face recognition: features versus templates

by Roberto Brunelli, Tomaso Poggio - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 1993
"... Over the last 20 years, several different techniques have been proposed for computer recognition of human faces. The purpose of this paper is to compare two simple but general strategies on a common database (frontal images of faces of 47 people: 26 males and 21 females, four images per person). We ..."
Abstract - Cited by 749 (25 self) - Add to MetaCart
Over the last 20 years, several different techniques have been proposed for computer recognition of human faces. The purpose of this paper is to compare two simple but general strategies on a common database (frontal images of faces of 47 people: 26 males and 21 females, four images per person

Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories

by Cordelia Schmid - In CVPR
"... This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingly fine sub-regions and computing histograms of local features found inside each sub-region. The resulting “spatial pyrami ..."
Abstract - Cited by 1923 (47 self) - Add to MetaCart
This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingly fine sub-regions and computing histograms of local features found inside each sub-region. The resulting “spatial

Local features and kernels for classification of texture and object categories: a comprehensive study

by J. Zhang, S. Lazebnik, C. Schmid - International Journal of Computer Vision , 2007
"... Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations an ..."
Abstract - Cited by 653 (34 self) - Add to MetaCart
Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a large-scale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations

Valgrind: A framework for heavyweight dynamic binary instrumentation

by Nicholas Nethercote, Julian Seward - In Proceedings of the 2007 Programming Language Design and Implementation Conference , 2007
"... Dynamic binary instrumentation (DBI) frameworks make it easy to build dynamic binary analysis (DBA) tools such as checkers and profilers. Much of the focus on DBI frameworks has been on performance; little attention has been paid to their capabilities. As a result, we believe the potential of DBI ha ..."
Abstract - Cited by 558 (5 self) - Add to MetaCart
register and memory value with another value that describes it. This support accounts for several crucial design features that distinguish Valgrind from other DBI frameworks. Because of these features, lightweight tools built with Valgrind run comparatively slowly, but Valgrind can be used to build more

From SHIQ and RDF to OWL: The Making of a Web Ontology Language

by Ian Horrocks, Peter F. Patel-Schneider, Frank Van Harmelen - Journal of Web Semantics , 2003
"... The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic W ..."
Abstract - Cited by 615 (39 self) - Add to MetaCart
The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic

Face description with local binary patterns: Application to face recognition

by Abdenour Hadid, Senior Member - IEEE Trans. Pattern Analysis and Machine Intelligence , 2006
"... Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a ..."
Abstract - Cited by 526 (27 self) - Add to MetaCart
Abstract—This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a

Approximate Riemann Solvers, Parameter Vectors, and Difference Schemes

by P. L. Roe - J. COMP. PHYS , 1981
"... Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution ..."
Abstract - Cited by 1010 (2 self) - Add to MetaCart
Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution

LLVM: A compilation framework for lifelong program analysis & transformation

by Chris Lattner, Vikram Adve , 2004
"... ... a compiler framework designed to support transparent, lifelong program analysis and transformation for arbitrary programs, by providing high-level information to compiler transformations at compile-time, link-time, run-time, and in idle time between runs. LLVM defines a common, low-level code re ..."
Abstract - Cited by 852 (20 self) - Add to MetaCart
representation in Static Single Assignment (SSA) form, with several novel features: a simple, language-independent type-system that exposes the primitives commonly used to implement high-level language features; an instruction for typed address arithmetic; and a simple mechanism that can be used to implement
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