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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： M. Bicego A. Lagorio E. Grosso M. Tistarelli University of Sassari Italy

Several pattern recognition and classification techniques have been applied to the biometrics domain. Among them, an interesting technique is the Scale Invariant Feature Transform (SIFT), originally devised for object recognition. Even if SIFT features have emerged as a very powerful image descriptors, their employment in face analysis context has never been systematically investigated. This paper investigates the application of the SIFT approach in the context of face authentication. In order to determine the real potential and applicability of the method, different matching schemes are proposed and tested using the BANCA database and protocol, showing promising results.

关键词： Authentication Face detection pattern recognition Face recognition Independent component analysis Biometrics Object recognition Image analysis Testing Image databases

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Genetic Algorithm SAmple Consensus (GASAC) - A Parallel Strategy for Robust Parameter Estimation

Genetic Algorithm SAmple Consensus (GASAC) - A Parallel Stra...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： V. Rodehorst O. Hellwich Computer Vision & Remote Sensing Berlin University of Technology Berlin Germany

A new robust estimator based on an evolutionary optimization technique is proposed. The general hypothesizeand- verify strategy accelerates the parameter estimation substantially by systematic trial and parallel evaluation without the use of prior information. The method is evaluated by estimation of multi-view relations, i.e. the fundamental matrix. Additionally, some results for the trifocal geometry are presented. However, the general methodology could be used for any problem in which relations can be determined from a minimum number of points.

关键词： Genetic algorithms Robustness Parameter estimation computer vision Maximum likelihood estimation Geometry Cost function Remote sensing pattern recognition conferences

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Reading LCD/LED Displays with a Camera Cell Phone

Reading LCD/LED Displays with a Camera Cell Phone

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Huiying Shen J. Coughlan Smith-Kettlewell Eye Research Institute San Francisco CA USA

Being able to read LCD/LED displays would be a very important step towards greater independence for persons who are blind or have low vision. A fast graphical model based algorithm is proposed for reading 7-segment digits in LCD/LED displays. The algorithm is implemented for Symbian camera cell phones in Symbian C++. The software reads one display in about 2 seconds by a push of a button on the cell phone (Nokia 6681, 220 MHz ARM CPU).

关键词： Light emitting diodes Liquid crystal displays Cameras Cellular phones computer vision Application software computer displays Smart phones Hardware Central Processing Unit

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Semantic-Shift for Unsupervised Object Detection

Semantic-Shift for Unsupervised Object Detection

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： D. Liu Tsuhan Chen Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA

The bag of visual words representation has attracted a lot of attention in the computer vision community. In particular, Probabilistic Latent Semantic Analysis (PLSA) has been applied to object recognition as an unsupervised technique built on top of the bag of visual words representation. PLSA, however, does not explicitly consider the spatial information of the visual words. In this paper, we propose an iterative technique, where a modified form of PLSA provides location and scale estimates of the foreground object through the estimated latent semantic. In return, the updated location and scale estimates will improve the estimate of the latent semantic. We call this iterative algorithm Semantic-Shift. We show results with significant improvements over PLSA.

关键词： Object detection computer vision Object recognition Unsupervised learning Graphical models Iterative algorithms Labeling Internet Clustering methods pattern recognition

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IEEE workshop on Privacy Research in vision (PRIV)

Proceedings of the IEEE Computer Society Conference on Compu...

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Proceedings of the IEEE computer Society conference on computer vision and pattern recognition 2006年 2006卷 35-35页

作者： Boult, T. Bowyer, K. Phillips, J. Ross, A. Avidan, S. Brown, L. Teoh, A.B.J. University of Colorado Colorado Springs United States National Inst. of Standards and Technology United States West Virginia University United States Mitsubishi Electric Research Lab. United States IBM Research Multimedia University Malaysia

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Coalitional Tracking in Facial Infrared Imaging and Beyond

Coalitional Tracking in Facial Infrared Imaging and Beyond

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： J. Dowdall I.T. Pavlidis P. Tsiamyrtzis Department of Computer Science University of Houston Houston TX USA Department of Statistics Athens University of Economics and Business Athens Greece

We propose a novel facial tracking method that uses a distributed network of individual trackers whose interactions are modeled using coalitional game theory. Our tracking method maintains a high level of accuracy and can negotiate surface deformations and occlusions. We tested the method on a substantial video set featuring non-trivial face motion from over 40 subjects in both the infrared and visual spectra. The coalitional tracker demonstrated fault tolerant behavior that exceeds by far the performance of single condensation trackers. Our method represents a shift from the typical tracking paradigms and may find broader application in demanding imaging problems across the electromagnetic spectrum.

关键词： Infrared imaging Target tracking computer vision pattern recognition conferences State estimation computer science Games Videoconference Fault tolerance

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Facial Action Coding Using Multiple Visual Cues and a Hierarchy of Particle Filters

Facial Action Coding Using Multiple Visual Cues and a Hierar...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： J.C. McCall M.M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

In this paper we present a framework for tracking nonrigid facial landmarks by combining various visual cues at multiple levels of detail. Using a probabilistic framework consisting of a hierarchy of particle filters, we are able to track individual facial landmarks using multiple visual cues at the local level, as well as tracking results at more coarse level of detail. This allows for the fusion of global and local cues in an efficient and robust manner. Testing is performed by tracking and classifying facial action codes obtained from the Cohn-Kanade AU-Coded Facial Expression Database.

关键词： Particle filters Face detection Robustness Particle tracking computer vision Intelligent vehicles Humans Magnetic heads Filtering Robot vision systems

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Attribute Grammar-Based Event recognition and Anomaly Detection

Attribute Grammar-Based Event Recognition and Anomaly Detect...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Seong-Wook Joo R. Chellappa Department of Computer Science Center for Automation Research University of Maryland College Park MD USA

We propose to use attribute grammars for recognizing normal events and detecting abnormal events in a video. Attribute grammars can describe constraints on features (attributes) in addition to the syntactic structure of the input. Events are recognized using an extension of the Earley parser that handles attributes and concurrent event threads. Abnormal events are detected when the input does not follow syntax of the grammar or the attributes do not satisfy the constraints in the attribute grammar to some degree. We demonstrate the effectiveness of our method for the task of recognizing normal events and detecting anomalies in a parking lot.

关键词： Event detection Hidden Markov models Stochastic processes Prototypes pattern recognition Yarn Error correction Statistics computer science Automation

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Fast and Adaptive Pairwise Similarities for Graph Cuts-based Image Segmentation

Fast and Adaptive Pairwise Similarities for Graph Cuts-based...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： B. Sumengen L. Bertelli B.S. Manjunath Ojos Inc. University of California Santa Barbara Santa Barbara CA USA

We introduce the use of geodesic distances and geodesic radius for calculating pairwise similarities needed in various graph cuts based methods. By using geodesics on an edge strength function we are able to calculate similarities between pixels in a more natural way. Our technique improves the speed and reliability of calculating similarities and leads to reasonably good image segmentation results. Our algorithm takes an edge strength function as its input and its speed is independent of the feature dimension or the distance measure used.

关键词： Image segmentation Partitioning algorithms Pixel Cost function Joining processes Velocity measurement Gray-scale Focusing computer vision pattern recognition

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Multiscale Modeling and Constraints for Max-flow/Min-cut Problems in computer vision

Multiscale Modeling and Constraints for Max-flow/Min-cut Pro...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： M.W. Turek D. Freedman Rensselaer Polytechnic Institute Troy NY USA

Multiscale techniques have been used for many years in computer vision. Recently multiscale edges have received attention in spectral graph methods as an important perceptual cue. In this paper multiscale cues are used in the context of max-flow/min-cut energy minimization. We formulate multiscale min-cut versions of three typical computer vision applications, namely interactive segmentation, image restoration, and optical flow. We then solve across all scales simultaneously. This use of multiscale models and constraints leads to quantitatively and qualitatively improved experimental results.

关键词： computer vision Image segmentation Image restoration Optical sensors Image motion analysis Application software Matrix decomposition Annealing Approximation algorithms Joining processes

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