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共 467 条记录，以下是71-80 订阅

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Illumination Invariant Elastic Bunch Graph Matching for Efficient Face recognition

Illumination Invariant Elastic Bunch Graph Matching for Effi...

引用

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

作者： N. Kela A. Rattani P. Gupta I. I. T. Kanpur India

This paper proposes a system which can handle illumination problem of face recognition systems by using "Retinex and color constancy" algorithm. The Retinex and color constancy approach has been plugged with Elastic Bunch Graph Matching (EBGM). The proposed system has been tested on IITK database having more than 1000 face images. The experimental results demonstrate that performance of the proposed system is superior to the known systems. The overall accuracy has shown an increase of 3.14% as compared to the known EBGM based recognition system without using Retinex and Color Constancy method.

关键词： Lighting Face recognition Independent component analysis Algorithm design and analysis Image databases Layout Humans Face detection pattern recognition Neural networks

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Semi-autonomous Learning of Objects

Semi-autonomous Learning of Objects

引用

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

作者： Hyundo Kim E. Murphy-Chutorian J. Triesch Complex Systems & Cognition Laboratory University of California San Diego La Jolla CA USA Frankfurt Institute for Advanced Studies Frankfurt Germany

This paper presents a robotic vision system that can be taught to recognize novel objects in a semi-autonomous manner that does not require manual labeling or segmentation of any individual training images. Instead, unfamiliar objects are simply shown to the system in varying poses and scales against cluttered background and the system automatically detects, tracks, segments, and builds representations for these objects. We demonstrate the feasibility of our approach by training the system to recognize one hundred household objects, which are presented to the system for about a minute each. Our method resembles the way that biological organisms learn to recognize objects and it paves the way for a wealth of applications in robotics and other fields.

关键词： Humans Image segmentation Machine vision Labeling Robot vision systems Robotics and automation Image recognition Biological systems computer vision Training data

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Dynamical Motion Vocabularies for Kinematic Tracking and Activity recognition

Dynamical Motion Vocabularies for Kinematic Tracking and Act...

引用

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

作者： O.C. Jenkins G. Gonzalez M. Loper Computer Science Department Brown University Providence RI USA

We present a method for 3D monocular kinematic pose estimation and activity recognition through the use of dynamical human motion vocabularies. A motion vocabulary is comprised as a set of primitives that each describe the movement dynamics of an activity in a low-dimensional space. Given image observations over time, each primitive is used to infer the pose independently using its expected dynamics in the context of a particle filter. Pose estimates from a set of primitives are inferred in parallel and arbitrated to estimate the activity being performed. The approach presented is evaluated through tracking and activity recognition over extended motion trials. The results suggest robustness with respect to multi-activity movement, movement speed, and camera viewpoint.

关键词： Vocabulary Kinematics Tracking Humans computer vision Particle filters State estimation Animation Bars Machine learning

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Factor Graphs for Region-based Whole-scene Classification

Factor Graphs for Region-based Whole-scene Classification

引用

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

作者： M.R. Boutell Jiebo Luo C.M. Brown CSSE Department Rose Hulman Institute of Technology USA Research and Development Laboratories Eastman Kodak (Japan) Limited USA Department of Computer Science University of Rochester USA

Semantic scene classification is still a challenging problem in computer vision. In contrast to the common approach of using low-level features computed from the scene, our approach uses explicit semantic object detectors and scene configuration models. To overcome faulty semantic detectors, it is critical to develop a region-based, generative model of outdoor scenes based on characteristic objects in the scene and spatial relationships between them. Since a fully connected scene configuration model is intractable, we chose to model pairwise relationships between regions and estimate scene probabilities using loopy belief propagation on a factor graph. We demonstrate the promise of this approach on a set of over 2000 outdoor photographs, comparing it with existing discriminative approaches and those using low-level features.

关键词： Layout Detectors computer science computer vision pattern recognition conferences Terminology Upper bound Maximum likelihood detection Object detection

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Analysis of Local Appearance-Based Face recognition: Effects of Feature Selection and Feature Normalization

Analysis of Local Appearance-Based Face Recognition: Effects...

引用

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

作者： H.K. Ekenel R. Stiefelhagen Interactive Systems Laboratories Computer Science Department Universität Karlsruhe Karlsruhe Germany

In this paper, the effects of feature selection and feature normalization to the performance of a local appearance based face recognition scheme are presented. From the local features that are extracted using block-based discrete cosine transform, three feature sets are derived. These local feature vectors are normalized in two different ways; by making them unit norm and by dividing each coefficient to its standard deviation that is learned from the training set. The input test face images are then classified using four different distance measures: L1 norm, L2 norm, cosine angle and covariance between feature vectors. Extensive experiments have been conducted on the AR and CMU PIE face databases. The experimental results show the importance of using appropriate feature sets and doing normalization on the feature vector.

关键词： Face recognition Discrete cosine transforms Feature extraction Face detection computer vision pattern recognition conferences Interactive systems computer science Performance analysis

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Synchronous Image Acquisition based on Network Synchronization

Synchronous Image Acquisition based on Network Synchronizati...

引用

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

作者： G. Litos X. Zabulis G. Triantafyllidis Informatics and Telematics Institute Thessaloniki Greece

In this paper, a software-based system for the real-time synchronization of images captured by a low-cost camera framework is presented. It is most well suited for cases where special hardware cannot be utilized (e.g. remote or wireless applications) and when cost efficiency is critical. The proposed method utilizes messages to establish a consensus on the time of image acquisition and NTP synchronization of computer clocks. It also provides with an error signal, in case of failure of the synchronization. The evaluation of the proposed algorithm using a precise LED array system (1ms accuracy) proves the effectiveness of this method.

关键词： Cameras Synchronization Hardware Application software Production computer aided manufacturing Real time systems computer errors Light emitting diodes computer vision

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A Comparison of 3D Biometric Modalities

A Comparison of 3D Biometric Modalities

引用

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

作者： D.L. Woodard T.C. Faltemier Ping Yan P.J. Flynn K.W. Bowyer Department of Computer Science and Engineering University of Notre Dame Notre Dame IN USA

Recently, researchers have focused on the use of threedimensional data as a source of distinguishing features for personal identification. In this paper, the recognition performance of three three-dimensional biometric modalities (face, ear, and finger surface) is compared. In addition, we combine the modalities in an attempt to improve overall recognition performance. The Iterative Closest Point (ICP) algorithm and root mean square (RMS) registration error are used to measure match quality in each case. The experimental results using a dataset of multi-modal biometric samples collected from a group of 85 individuals are presented.

关键词： Biometrics Ear Fingers Iterative closest point algorithm Face recognition Iterative algorithms Lighting Principal component analysis Image segmentation Image recognition

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Historical Perspectives on 4D Virtualized Reality

Historical Perspectives on 4D Virtualized Reality

引用

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

作者： T. Kanade P.J. Narayanan Carnegie Mellon University Pittsburgh PA USA Centre for Visual Information Technology International Institute of Information Technology Hyderabad India

Recording dynamic events, such as a sports event, a ballet performance, or a lecture, digitally for experiencing in a spatiotemporally distant setting requires 4D capture: three dimensions for their geometry/ appearance over the fourth dimension of time. Cameras are suitable for this task as they are nonintrusive, universal, and inexpensive. computer vision techniques have advanced sufficiently to make the 4D capture possible. In this paper, we present a historical perspective on the Virtualized RealityTM system developed since early 90s to early 2000 at CMU for the 4D capture of dynamic events.

关键词： Layout Cameras computer vision Information technology Spatiotemporal phenomena Navigation Videos Robots Geometry computer science education

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Salient Contour Detection using a Global Contour Discontinuity Measurement

Salient Contour Detection using a Global Contour Discontinui...

引用

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

作者： Hongzhi Wang J. Oliensis Stevens Institute of Technology USA

Salient contour grouping/detection is one of the major topics in perceptual organization exploring the true meanings for contours. Extending contour’s discontinuity quality from low level discontinuity, we introduce a new perspective that a salient contour represents a sharp change in the ability to organize the image into meaningful parts. This new view gives a novel, general edge energy measure, which has important perceptual meanings. A new multiscale saliency function and its variational solution are also described. Experiments on real images validate our method.

关键词： Image edge detection Energy measurement Image segmentation Statistics Statistical distributions Shape Detectors Length measurement Gaussian processes computer vision

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Using Spatio-Temporal Patches for Simultaneous Estimation of Edge Strength, Orientation, and Motion

Using Spatio-Temporal Patches for Simultaneous Estimation of...

引用

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

作者： A.N. Stein M. Hebert The Robotics Institute Carnegie Mellon University Pittsburgh PA USA

We describe an extension to ordinary patch-based edge detection in images using spatio-temporal volumetric patches from video. The inclusion of temporal information enables us to estimate motion normal to edges in addition to edge strength and spatial orientation. The method can handle complex edges in clutter by comparing distributions of data on either half of an extracted patch, rather than modeling the intensity profile of the edge. An efficient approach is provided for building the necessary histograms which samples candidate edge orientations and motions. Results are compared to classical spatio-temporal filtering techniques.

关键词： Motion estimation Image edge detection Filters Filtering Layout computer vision Data mining Histograms Object recognition Detectors

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