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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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Robust face detection with multi-class boosting

Robust face detection with multi-class boosting

引用

conference on computer vision and pattern recognition (cvpr)

作者： Yen-Yu Lin Tyng-Luh Liu Institute of Information Science Academia Sinica Taipei Taiwan

ISBN: (纸本)0769523722

With the aim to design a general learning framework for detecting faces of various poses or under different lighting conditions, we are motivated to formulate the task as a classification problem over data of multiple classes. Specifically, our approach focuses on a new multi-class boosting algorithm, called MBHboost, and its integration with a cascade structure for effectively performing face detection. There are three main advantages of using MBHboost: 1) each MBH weak learner is derived by sharing a good projection direction such that each class of data has its own decision boundary; 2) the proposed boosting algorithm is established based on an optimal criterion for multi-class classification; and 3) since MBHboost is flexible with respect to the number of classes, it turns out that it is possible to use only one single boosted cascade for the multi-class detection. All these properties give rise to a robust system to detect faces efficiently and accurately.

关键词： Robustness Face detection Boosting Detectors Neural networks Information science Multi-layer neural network Multilayer perceptrons Testing computer vision

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Optimal sub-shape models by minimum description length

Optimal sub-shape models by minimum description length

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria

Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. However, due to the linearity of PCA, non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably. Although non-linear extensions of active shape models have been proposed and application specific solutions have been used, they still need a certain amount of user interaction during model building. In this paper the task of building/choosing optimal models is tackled in a more generic information theoretic fashion. In particular, we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts, each adequate for linear modeling. This results in an overall more compact model configuration. Which in turn leads to a better model in terms of modes of variations. The proposed method is evaluated on synthetic data, medical images and hand contours.

关键词： Active shape model Biomedical imaging Principal component analysis computer vision Linearity Polynomials pattern recognition computer graphics Radiology Image processing

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Single Camera Stereo for Mobile Robot Surveillance

Single Camera Stereo for Mobile Robot Surveillance

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： J. McBride M. Snorrason T. Goodsell R. Eaton M.R. Stevens Charles River Analytics 슠Inc. Cambridge MA USA

Mobile robot designers frequently look to computer vision to solve navigation, obstacle avoidance, and object detection problems such as those encountered in parking lot surveillance. Stereo reconstruction is a useful technique in this domain. The advantage of a single-camera stereo method versus a stereo rig is the flexibility to change the baseline distance to best match each scenario. This directly increases the robustness of the stereo algorithm and increases the effective range of the system. The challenge comes from accurately rectifying the images into an ideal stereo pair. Structure from motion (SFM) can be used to compute the camera motion between the two images, but its accuracy is limited and small errors can cause rectified images to be misaligned. We present a single-camera stereo system that incorporates a Levenberg-Marquardt minimization of rectification parameters to bring the rectified images into alignment.

关键词： Robot vision systems Cameras Mobile robots Surveillance Stereo vision computer vision Navigation Object detection Stereo image processing Image reconstruction

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A combined physical and statistical approach to colour constancy

A combined physical and statistical approach to colour const...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Schaefer S. Hordley G. Finlayson School of Computing and Informatics Nottingham Trent University UK School of Computing Sciences University of East Anglia UK

Computational colour constancy tries to recover the colour of the scene illuminant of an image. Colour constancy algorithms can, in general, be divided into two groups: statistics-based approaches that exploit statistical knowledge of common lights and surfaces, and physics-based algorithms which are based on an understanding of how physical processes such as highlights manifest themselves in images. A combined physical and statistical colour constancy algorithm that integrates the advantages of the statistics-based colour by correlation method with those of a physics-based technique based on the dichromatic reflectance model is introduced. In contrast to other approaches not only a single illuminant estimate is provided but a set of likelihoods for a given illumination set. Experimental results on the benchmark Simon Fraser image database show the combined method to clearly outperform purely statistical and purely physical algorithms.

关键词： Neural networks Layout Reflectivity Lighting Image databases computer vision Informatics Color Correlation Digital cameras

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Face verification across age progression

Face verification across age progression

引用

conference on computer vision and pattern recognition (cvpr)

作者： N. Ramanathan R. Chellappa ECE Department University of Maryland College Park USA

Human faces undergo considerable amount of variations with aging. While studies have revealed the extent to which factors such as illumination variations, pose variations, facial expression and occlusions affect face recognition, the role of natural factors such as aging effects in affecting the same are yet to be studied. How does age progression affect the similarity between two images of an individual? What is the confidence associated with establishing the identity between two age separated face images of an individual? On a database of pairs of passport images, we study similarity of faces as a function time. We propose a Bayesian age-difference classifier that is built on a probabilistic eigenspaces framework. Since age separated face images invariably differ in illumination and have facial variations due to aging, we propose a method to overcome non uniform illumination across face images. The problem discussed in this paper has direct applications in passport renewal and homeland security.

关键词： Aging Face recognition Humans Shape Lighting Face detection Educational institutions Image databases Capacitive sensors Pixel

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A Real-Time Human Stress Monitoring System Using Dynamic Bayesian Network

A Real-Time Human Stress Monitoring System Using Dynamic Bay...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Wenhui Liao Weihong Zhang Zhiwei Zhu Qiang Ji Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

We present a real time non-invasive system that infers user stress level from evidences of different modalities. The evidences include physical appearance (facial expression, eye movements, and head movements) extracted from video via visual sensors, physiological conditions collected from an emotional mouse, behavioral data from user interaction activities with the computer, and performance measures. We provide a Dynamic Bayesian Network (DBN) framework to model the user stress and these evidences. We describe the computer vision techniques we used to extract the visual evidences, the DBN model for modeling stress and the associated factors, and the active sensing strategy to collect the most informative evidences for efficient stress inference. Our experiments show that the inferred user stress level by our system is consistent with that predicted by psychological theories.

关键词： Real time systems Stress Bayesian methods Human factors Data mining Biomedical monitoring Mice Physics computing computer vision Psychology

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Modelling reflections via multiperspective imaging

Modelling reflections via multiperspective imaging

引用

conference on computer vision and pattern recognition (cvpr)

作者： Jingyi Yu L. McMillan Massachusetts Institute of Technology Cambridge MA USA University of North Carolina Chapel Hill Chapel Hill NC USA

We present a novel method for analyzing reflections on arbitrary surfaces. We model reflections using a broader than usual class of imaging models, which include both perspective and multiperspective camera types. We provide an analytical framework to locally model reflections as specific multiperspective cameras around every ray based on a new theory of general linear cameras. Our framework better characterizes the complicated image distortions seen on irregular mirror surfaces as well as the conventional catadioptric mirrors. We show the connection between multiperspective camera models and caustic surfaces of reflections and demonstrate how they reveal important surface rulings of the caustics. Finally, we show how to use our analysis to assist mirror design and characterize distortions seen in catadioptric imaging systems.

关键词： Optical reflection Cameras Mirrors Optical imaging Image analysis computer vision Optical distortion Potential well Physics Geometry

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Using the inner-distance for classification of articulated shapes

Using the inner-distance for classification of articulated s...

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conference on computer vision and pattern recognition (cvpr)

作者： H. Ling D.W. Jacobs Computer Science Department University of Maryland College Park USA

We propose using the inner-distance between landmark points to build shape descriptors. The inner-distance is defined as the length of the shortest path between landmark points within the shape silhouette. We show that the inner-distance is articulation insensitive and more effective at capturing complex shapes with part structures than Euclidean distance. To demonstrate this idea, it is used to build a new shape descriptor based on shape contexts. After that, we design a dynamic programming based method for shape matching and comparison. We have tested our approach on a variety of shape databases including an articulated shape dataset, MPEG7 CE-Shape-1, Kimia silhouettes, a Swedish leaf database and a human motion silhouette dataset. In all the experiments, our method demonstrates effective performance compared with other algorithms.

关键词： Euclidean distance Dynamic programming Databases Shape measurement Testing Jacobian matrices computer science Educational institutions MPEG 7 Standard Humans

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Improved Likelihood Function in Particle-based IR Eye Tracking

Improved Likelihood Function in Particle-based IR Eye Tracki...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： D. Witzner Hansen R. Satria J. Sorensen R. Hammoud Dept. of Innovation IT University Copenhagen Denmark Delphi Electronics and Safety Kokomo Indiana USA Dept. of Innovation IT University Copenhagen

In this paper we propose a log likelihood-ratio function of foreground and background models used in a particle filter to track the eye region in dark-bright pupil image sequences. This model fuses information from both dark and bright pupil images and their difference image into one model. Our enhanced tracker overcomes the issues of prior selection of static thresholds during the detection of feature observations in the bright-dark difference images. The auto-initialization process is performed using cascaded classifier trained using adaboost and adapted to IR eye images. Experiments show good performance in challenging sequences with test subjects showing large head movements and under significant light conditions.

关键词： Particle tracking Lighting Face detection Eyes Layout Light sources computer vision Head Humans Robustness

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Extended-Regular Sequence for Automated Analysis of Microarray Images

Extended-Regular Sequence for Automated Analysis of Microarr...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Hee-Jeong Jin Bong-Kyung Chun Hwan-Gue Cho Department of Computer Engineering Pusan National University busan South Korea

A variety of high throughput methods have made it possible to generate detailed temporal expression data for a single gene or large numbers of genes. Methods for analysis of these large data sets can be problematic. One challenge is the comparison of temporal expression data obtained from different growth conditions where the patterns of expression may be shifted in time. We propose the use of wavelet analysis to transform the data obtained under different growth conditions to permit comparison of expression patterns from experiments that have time shifts or delays. We demonstrate this approach using detailed temporal data for a single bacterial gene obtained under 72 different growth conditions. This general strategy for can be applied in the analysis of data sets of thousands of genes during cellular differentiation and response.

关键词： Image analysis Image sequence analysis Throughput Wavelet analysis pattern analysis Wavelet transforms Delay effects Propagation delay Microorganisms Data analysis

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