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Global and local quality measures for NIR iris video

Global and local quality measures for NIR iris video

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Jinyu Zuo Natalia A. Schmid Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV USA

In the field of iris-based recognition, evaluation of quality of images has a number of important applications. These include image acquisition, enhancement, and data fusion. Iris image quality metrics designed for these applications are used as figures of merit to quantify degradations or improvements in iris images due to various image processing operations. This paper elaborates on the factors and introduces new global and local factors that can be used to evaluate iris video and image quality. The main contributions of the paper are as follows. (1) A fast global quality evaluation procedure for selecting the best frames from a video or an image sequence is introduced. (2) A number of new local quality measures for the iris biometrics are introduced. The performance of the individual quality measures is carefully analyzed. Since performance of iris recognition systems is evaluated in terms of the distributions of matching scores and recognition probability of error, from a good iris image quality metric it is also expected that its performance is linked to the recognition performance of the biometric recognition system.

关键词： Iris Image quality Biometrics Image recognition Image segmentation Application software Q factor Electric variables measurement computer science Degradation

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A method for selecting and ranking quality metrics for optimization of biometric recognition systems

A method for selecting and ranking quality metrics for optim...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Natalia A. Schmid Francesco Nicolo Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV USA

In the field of biometrics evaluation of quality of biometric samples has a number of important applications. The main applications include (1) to reject poor quality images during acquisition, (2) to use as enhancement metric, and (3) to apply as a weighting factor in fusion schemes. Since a biometric-based recognition system relies on measures of performance such as matching scores and recognition probability of error, it becomes intuitive that the metrics evaluating biometric sample quality have to be linked to the recognition performance of the system. The goal of this work is to design a method for evaluating and ranking various quality metrics applied to biometric images or signals based on their ability to predict recognition performance of a biometric recognition system. The proposed method involves: (1) Preprocessing algorithm operating on pairs of quality scores and generating relative scores, (2) Adaptive multivariate mapping relating quality scores and measures of recognition performance and (3) Ranking algorithm that selects the best combinations of quality measures. The performance of the method is demonstrated on face and iris biometric data.

关键词： Optimization methods Biometrics Image recognition Image quality Design methodology Iris Image coding Application software Signal design Video compression

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Towards Unlocking Web Video: Automatic People Tracking and Clustering

Towards Unlocking Web Video: Automatic People Tracking and C...

引用

ieee computer society conference on computer vision and pattern recognition workshops

作者： Alex Holub Pierre Moreels Atiq Islam Andrei Makhanov Rui Yang Ooyala Inc CA

ISBN: (纸本)9781424439942

This paper describes a system for automatically extracting meta-information on people from videos on the web. The system contains multiple modules which automatically track people, including both faces and bodies, and clusters the people into distinct groups. We present new technology and significantly modify existing algorithms for body-detection, shot-detection and grouping, tracking, and track-clustering within our system. The system was designed to work effectivity on web content, and thus exhibits robust tracking and clustering behavior over a broad spectrum of professional and semi-professional video content. In order to quantify and evaluate our system we created a large ground-truth data-set of people within video. Finally, we provide actual video examples of our algorithm and find that the results are quite strong over a broad range of content.

关键词： Face detection computer vision Clustering algorithms Solids Image recognition Robustness Application software Information filtering Information filters Object recognition

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Dominance detection in face-to-face conversations

Dominance detection in face-to-face conversations

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Sergio Escalera Rosa M. Martinez Jordi Vitria Petia Radeva M. Teresa Anguera Department Matemàtiques Universitat de Barcelona Barcelona Spain Computer Vision Center Campus UAB Barcelona Spain Department Metodologia de les Ciències del Comportament Universitat de Barcelona Barcelona Spain

Dominance is referred to the level of influence a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on dominance detection from visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers opinion. Moreover, the considered indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analysis shows a high correlation and allows the categorization of dominant people in public discussion video sequences.

关键词： Face detection Psychology Wearable computers Video sequences Speech Feature extraction computer vision Context Displays Face recognition

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ieee computer society conference on computer vision and pattern recognition workshops

IEEE Computer Society Conference on Computer Vision and Patt...

引用

conference on computer vision and pattern recognition Workshop, CVPRW 2003

ISBN: (纸本)0769519008

The proceedings contain 99 papers. The topics discussed include: fast fragment assemblage using boundary line and surface matching;archaeological fragment reconstruction using curve-matching;profile-based pottery reconstruction;accurately estimating sherd 3D surface geometry with application to pot reconstruction;application of structured illumination in nano-scale vision;noise adaptive channel smoothing of low-dose images;indirect symbolic correlation approach to unsegmented text recognition;background line detection with a stochastic model;estimating tracking sources and sinks;generic event detection in sports video using cinematic features;towards perceptual interface for visualization navigation of large data sets;coevolutionary computation for synthesis of recognition systems;mirror shape recovery from image curves and intrinsic parameters: rotationally symmetric and conic mirrors;parametric subpixel matchpoint recovery with uncertainty estimation: a statistical approach;and tracking random sets of vehicles in terrain.

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ieee computer society conference on computer vision and pattern recognition workshops

IEEE Computer Society Conference on Computer Vision and Patt...

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conference on computer vision and pattern recognition Workshop, CVPRW 2003

ISBN: (纸本)0769519008

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