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检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013"

共 656 条记录，以下是231-240 订阅

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Computationally Efficient Face Spoofing Detection with Motion Magnification

Computationally Efficient Face Spoofing Detection with Motio...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Bharadwaj, Samarth Dhamecha, Tejas I. Vatsa, Mayank Singh, Richa IIIT Delhi Delhi India

ISBN: (纸本)9780769549903

For a robust face biometric system, a reliable anti-spoofing approach must be deployed to circumvent the print and replay attacks. Several techniques have been proposed to counter face spoofing, however a robust solution that is computationally efficient is still unavailable. this paper presents a new approach for spoofing detection in face videos using motion magnification. Eulerian motion magnification approach is used to enhance the facial expressions commonly exhibited by subjects in a captured video. Next, two types of feature extraction algorithms are proposed: (i) a configuration of LBP that provides improved performance compared to other computationally expensive texture based approaches and (ii) motion estimation approach using HOOF descriptor. On the Print Attack and Replay Attack spoofing datasets, the proposed framework improves the state-of-art performance;especially HOOF descriptor yielding a near perfect half total error rate of 0% and 1.25% respectively.

关键词： biometrics (access control) computer crime face recognition feature extraction image enhancement image texture motion estimation video databases video signal processing

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Visible-Spectrum Gaze Tracking for Sports

Visible-Spectrum Gaze Tracking for Sports

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Pires, Bernardo R. Hwangbo, Myung Devyver, Michael Kanade, Takeo Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9780769549903

In sports, wearable gaze tracking devices can enrich the viewer experience and be a powerful training tool. Because devices can be used for long periods of time, often outside, it is desirable that they do not use active illumination (infra-red light sources) for safety reasons and to minimize the interference of the sun. Unlike traditional wearable devices, in sports, the gaze tracking method must be robust to (often dramatic) movements of the user in relation to the device (i.e. the common assumption that, because the device is wearable, the eye does not move with regards to the camera no longer holds.) this paper extends a visible-spectrum gaze tracker in the literature to handle the requirements of a motor-sports application. Specifically, the method presented removes the original assumption (in the original method) that the eye position is fixed, and proposes the use of template matching to allow for changes in the eye location from frame to frame. Experimental results demonstrate that the proposed method can handle severe changes in the eye location and is very fast to compute (up to 60 frames per second in modern hardware.)

关键词： eye image matching interference iris recognition object tracking safety sport

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Exploiting Unlabeled Ages for Aging pattern Analysis on A Large Database

Exploiting Unlabeled Ages for Aging Pattern Analysis on A La...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Zhang, Chao Guo, Guodong W Virginia Univ Lane Dept CSEE Morgantown WV 26506 USA

ISBN: (纸本)9780769549903

"Big Data" analysis is an emerging topic in computer vision and pattern recognition. As one example problem of big data, we study semantic age labels and facial aging pattern analysis on a large database. In aging analysis, one of the great challenges is the lack of a large number of face images with ground truth age labels. Unlike many other example-based recognition problems where human annotations can be used as the ground truth labels for both training and testing, it is quite difficult to label the exact ages in face images by human annotators. An alternative is to exploit the unlabeled ages to enhance the age estimation performance. However, it is unclear whether the face images with unlabeled ages can be used or not for age estimation, and how to use the unlabeled data. In this paper, we study the two problems comprehensively under two paradigms: the semi-supervised learning and unsupervised learning for aging pattern analysis. We emphasize the importance of using ground truth age labels and a large database in order to derive a meaningful measure in the context of big data. Our study can make an impact on collecting aging patterns that is very expensive and time consuming in practice.

关键词： computer vision data analysis face recognition unsupervised learning visual databases

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PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors

PISA: Pixelwise Image Saliency by Aggregating Complementary ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Shi, Keyang Wang, Keze Lu, Jiangbo Lin, Liang Sun Yat Sen Univ Guangzhou 510275 Guangdong Peoples R China Advanced Digital Sci Cte Singapore Singapore

ISBN: (纸本)9780769549897

Driven by recent vision and graphics applications such as image segmentation and object recognition, assigning pixel-accurate saliency values to uniformly highlight foreground objects becomes increasingly critical. More often, such fine-grained saliency detection is also desired to have a fast runtime. Motivated by these, we propose a generic and fast computational framework called PISA - Pixelwise Image Saliency Aggregating complementary saliency cues based on color and structure contrasts with spatial priors holistically. Overcoming the limitations of previous methods often using homogeneous superpixel-based and color contrast-only treatment, our PISA approach directly performs saliency modeling for each individual pixel and makes use of densely overlapping, feature-adaptive observations for saliency measure computation. We further impose a spatial prior term on each of the two contrast measures, which constrains pixels rendered salient to be compact and also centered in image domain. By fusing complementary contrast measures in such a pixelwise adaptive manner, the detection effectiveness is significantly boosted. Without requiring reliable region segmentation or post-relaxation, PISA exploits an efficient edge-aware image representation and filtering technique and produces spatially coherent yet detail-preserving saliency maps. Extensive experiments on three public datasets demonstrate PISA's superior detection accuracy and competitive runtime speed over the state-of-the-arts approaches.

关键词： computer vision edge detection feature extraction filtering theory image colour analysis image representation image resolution image segmentation object detection object recognition rendering (computer graphics)

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A semi-automatic methodology for facial landmark annotation

A semi-automatic methodology for facial landmark annotation

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Sagonas, Cliristos Tzimiropoulos, Georgios Zafeiriou, Stefanos Pantic, Maja Imperial Coll London Dept Comp London England

ISBN: (纸本)9780769549903

Developing powerful deformable face models requires massive, annotated face databases on which techniques can be trained, validated and tested. Manual annotation of each facial image in terms of landmarks requires a trained expert and the workload is usually enormous. Fatigue is one of the reasons that in some cases annotations are inaccurate. this is why, the majority of existing facial databases provide annotations for a relatively small subset of the training images. Furthermore, there is hardly any correspondence between the annotated landmarks across different databases. these problems make cross-database experiments almost infeasible. To overcome these difficulties, we propose a semi-automatic annotation methodology for annotating massive face datasets. this is the first attempt to create a tool suitable for annotating massive facial databases. We employed our tool for creating annotations for MultiPIE, XM2VTS, AR, and FRGC Ver. 2 databases. the annotations will be made publicly available from http://***/resources/facial-point-annotations/. Finally, we present experiments which verify the accuracy of produced annotations.

关键词： face recognition image retrieval visual databases

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3D R Transform on Spatio-Temporal Interest Points for Action recognition

3D <i>R</i> Transform on Spatio-Temporal Interest Points for...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Yuan, Chunfeng Li, Xi Hu, Weiming Ling, Haibin Maybank, Stephen Natl Lab Pattern Recognit Inst Automat Beijing Peoples R China Univ Adelaide Sch Comp Sci Adelaide SA 5005 Australia Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Birkbeck Coll Sch Comp Sci & Informat Syst London WC1E 7HX England

ISBN: (纸本)9780769549897

Spatio-temporal interest points serve as an elementary building block in many modern action recognition algorithms, and most of them exploit the local spatio-temporal volume features using a Bag of Visual Words (BOVW) representation. Such representation, however, ignores potentially valuable information about the global spatio-temporal distribution of interest points. In this paper, we propose a new global feature to capture the detailed geometrical distribution of interest points. It is calculated by using the R transform which is defined as an extended 3D discrete Radon transform, followed by applying a two-directional two-dimensional principal component analysis. Such R feature captures the geometrical information of the interest points and keeps invariant to geometry transformation and robust to noise. In addition, we propose a new fusion strategy to combine the R feature with the BOVW representation for further improving recognition accuracy. We utilize a context-aware fusion method to capture both the pairwise similarities and higher-order contextual interactions of the videos. Experimental results on several publicly available datasets demonstrate the effectiveness of the proposed approach for action recognition.

关键词： Radon transforms computational geometry feature extraction image motion analysis image representation

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Bacteria Foraging Fusion For Face recognition Across Age Progression

Bacteria Foraging Fusion For Face Recognition Across Age Pro...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Yadav, Daksha Vatsa, Mayank Singh, Richa Tistarelli, Massimo IIIT Delhi Delhi India Univ Sassari I-07100 Sassari Italy

ISBN: (纸本)9780769549903

the phenomenon of "aging" in humans leads to significant variations in facial features. Various factors such as bone growth, ethnicity and dietary habits influence the facial aging pattern. this increases the difficulty in performing automated face recognition. In this paper, we propose an algorithm that improves the performance of face recognition by applying the bacteria foraging fusion algorithm. the proposed algorithm mitigates the effect of facial changes caused due to aging by combining the LBP features of global and local facial regions at match score level, by means of the bacteria foraging fusion algorithm. Experimental results are presented using the FG-Net and IIITDelhi face aging databases. the IIITDelhi database, which has been collected by the authors, consists of over 2600 age-separated labeled face images of 102 individuals. To account for real life and natural conditions, images include changes in the face due to illumination, pose, and presence of accessories such as eyeglasses. the results demonstrate that the proposed approach outperforms traditional fusion schemes, existing algorithms and a commercial system.

关键词： age issues face recognition feature extraction image fusion lighting pose estimation

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Robust Estimation of Nonrigid Transformation for Point Set Registration

Robust Estimation of Nonrigid Transformation for Point Set R...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Ma, Jiayi Zhao, Ji Tian, Jinwen Tu, Zhuowen Yuille, Alan L. Huazhong Univ Sci & Technol Wuhan Peoples R China Univ Calif Los Angeles Dept Stat Los Angeles CA USA CMU Inst Robot Pittsburgh PA USA Univ Calif Los Angeles Lab Neuro Imaging Los Angeles CA 90024 USA

ISBN: (纸本)9780769549897

We present a new point matching algorithm for robust nonrigid registration. the method iteratively recovers the point correspondence and estimates the transformation between two point sets. In the first step of the iteration, feature descriptors such as shape context are used to establish rough correspondence. In the second step, we estimate the transformation using a robust estimator called L2E. this is the main novelty of our approach and it enables us to deal with the noise and outliers which arise in the correspondence step. the transformation is specified in a functional space, more specifically a reproducing kernel Hilbert space. We apply our method to nonrigid sparse image feature correspondence on 2D images and 3D surfaces. Our results quantitatively show that our approach outperforms state-of-the-art methods, particularly when there are a large number of outliers. Moreover, our method of robustly estimating transformations from correspondences is general and has many other applications.

关键词： Hilbert spaces image matching image registration shape recognition

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Not Everybody's Special: Using Neighbors in Referring Expressions with Uncertain Attributes

Not Everybody's Special: Using Neighbors in Referring Expres...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Sadovnik, Amir Gallagher, Andrew Chen, Tsuhan Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

ISBN: (纸本)9780769549903

Referring expression generation is widely considered a basic building block of any natural language generation system. Generating these phrases, which can point out a single object from a group of objects, has been studied extensively in that community. However, to build systems which can discuss images in an intelligent way, it is necessary to consider additional factors unique to the visual domain. In this paper we consider the use of neighbors as anchors to create a referring expression for a person in a group image. We describe a target person using the people around him, when we cannot find a reliable set of attributes to describe the target himself. We first present a method for including neighbors in a referring expression, and discuss several ways of presenting this data to a user. We show through experiments that using descriptions with neighbors can significantly improve the probability of conveying the correct information to a user.

关键词： gesture recognition natural language processing probability

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Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems

Multi-resolution Shape Analysis via Non-Euclidean Wavelets: ...

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26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Kim, Won Hwa Chung, Moo K. Singh, Vikas Univ Wisconsin Dept Comp Sci 1210 W Dayton St Madison WI 53706 USA Univ Wisconsin Dept Biostat & Med Informat Madison WI USA

ISBN: (纸本)9780769549897

the analysis of 3-D shape meshes is a fundamental problem in computer vision, graphics, and medical imaging. Frequently, the needs of the application require that our analysis take a multi-resolution view of the shape's local and global topology, and that the solution is consistent across multiple scales. Unfortunately, the preferred mathematical construct which offers this behavior in classical image/signal processing, Wavelets, is no longer applicable in this general setting (data with non-uniform topology). In particular, the traditional definition does not allow writing out an expansion for graphs that do not correspond to the uniformly sampled lattice (e.g., images). In this paper, we adapt recent results in harmonic analysis, to derive Non-Euclidean Wavelets based algorithms for a range of shape analysis problems in vision and medical imaging. We show how descriptors derived from the dual domain representation offer native multi-resolution behavior for characterizing local/global topology around vertices. With only minor modifications, the framework yields a method for extracting interest/key points from shapes, a surprisingly simple algorithm for 3-D shape segmentation (competitive with state of the art), and a method for surface alignment (without landmarks). We give an extensive set of comparison results on a large shape segmentation benchmark and derive a uniqueness theorem for the surface alignment problem.

关键词： computer vision feature extraction image representation image resolution image segmentation mesh generation wavelet transforms

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