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2010 IEEE computer Society Conference on computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Tong, Yan Wheeler, Frederick W. Liu, Xiaoming Visualization and Computer Vision Lab GE Global Research Niskayuna NY United States

ISBN: (纸本)9781424470297

Multi-modal biometric fusion is more accurate and reliable compared to recognition using a single biometric modality. However, most existing fusion approaches neglect the influence of the qualities of the biometric samples in information fusion. Our goal is to advance the state-of-the-art in biometric fusion technology by providing a more universal and more accurate solution for personal identification and verification with predictive quality metrics. In this work, we developed score-level multi-modal fusion algorithms based on predictive quality metrics and employed them for the task of face and fingerprint biometric fusion. The causal relationships in the context of the fusion scenario are modeled by Bayesian Networks. The recognition/verification decision is then made through probabilistic inference. Our experiments demonstrated that the proposed score-level fusion algorithms significantly improve the verification performance over the methods based on the raw match score of a single modality (face or fingerprint). Furthermore, the fusion framework with both face and fingerprint image qualities achieves the best verification performance and outperforms all other baseline fusion algorithms tested including other straightforward quality-based fusion methods. © 2010 IEEE.

关键词： Biometrics

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Optimal gradient pursuit for face alignment

Optimal gradient pursuit for face alignment

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IEEE International Conference on Automatic Face and Gesture Recognition

作者： Liu, Xiaoming Visualization and Computer Vision Lab GE Global Research Niskayuna NY 12309 United States

ISBN: (纸本)9781424491407

Face alignment aims to fit a deformable landmark-based mesh to a facial image so that all facial features can be located accurately. In discriminative face alignment, an alignment score function, which is treated as the appearance model, is learned such that moving along its gradient direction can improve the alignment. This paper proposes a new face model named Optimal Gradient Pursuit Model, where the objective is to minimize the angle between the gradient direction and the vector pointing toward the ground-truth shape parameter. We formulate an iterative approach to solve this minimization problem. With extensive experiments in generic face alignment, we show that our model improves the alignment accuracy and speed compared to the state-of-the-art discriminative face alignment approach. © 2011 IEEE.

关键词： Alignment

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LPSM: Fitting shape model by linear programming

LPSM: Fitting shape model by linear programming

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IEEE International Conference on Automatic Face and Gesture Recognition

作者： Tu, Jilin Laflen, Brandon Liu, Xiaoming Bello, Musodiq Rittscher, Jens Tu, Peter Visualization and Computer Vision Lab General Electric 1 Research Circle Niskayuna NY United States

ISBN: (纸本)9781424491407

We propose a shape model fitting algorithm that uses linear programming optimization. Most shape model fitting approaches (such as ASM, AAM) are based on gradient-descent-like local search optimization and usually suffer from local minima. In contrast, linear programming (LP) techniques achieve globally optimal solution for linear problems. In [1], a linear programming scheme based on successive convexification was proposed for matching static object shape in images among cluttered background and achieved very good performance. In this paper, we rigorously derive the linear formulation of the shape model fitting problem in the LP scheme and propose an LP shape model fitting algorithm (LPSM). In the experiments, we compared the performance of our LPSM with the LP graph matching algorithm(LPGM), ASM, and a CONDENSATION based ASM algorithm on a test set of PUT database. The experiments show that LPSM can achieve higher shape fitting accuracy. We also evaluated its performance on the fitting of some real world face images collected from internet. The results show that LPSM can handle various appearance outliers and can avoid local minima problem very well, as the fitting is carried out by LP optimization with l1 norm robust cost function. © 2011 IEEE.

关键词： Linear programming

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Image comparison by compound disjoint information

Image comparison by compound disjoint information

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2006 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2006

作者： Sun, Zhaohui Hoogs, Anthony Visualization and Computer Vision Lab. GE Global Research One Research Circle Niskayuna NY 12309

ISBN: (纸本)0769525970

In this paper, we study disjoint information as a metric for image comparison and its applications in image matching, alignment, and video tracking. Disjoint information is the joint entropy of random variables excluding the mutual information. This measure of statistical dependence and information redundancy satisfies more rigorous metric conditions than mutual information. For image comparison, compound disjoint information is derived from the marginal densities of the image distributions. By using marginal densities other than color histograms, it can overcome the difficulties (such as a lack of spatial information) inherent in histogram-based mutual information methods and enrich the vocabulary of image description. Disjoint information is not sensitive to illumination and appearance changes, and it is particularly suited for multimodal applications. © 2006 IEEE.

关键词： Image analysis

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Improved face model fitting on video sequences

Improved face model fitting on video sequences

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2007 18th British Machine vision Conference, BMVC 2007

作者： Liu, Xiaoming Wheeler, Frederick W. Tu, Peter H. Visualization and Computer Vision Lab General Electric Global Research Center Niskayuna NY 12309 United States

ISBN: (纸本)1901725340

Active Appearance Models (AAMs) represent the shape and appearance of an object via two low-dimensional subspaces, one for shape and one for appearance. AAMs for facial images are currently receiving considerable attention from the computer vision community. However, most existing work focuses on fitting AAMs to a single image. For many applications, effectively fitting an AAM to video sequences is of critical importance and challenging, especially considering the varying quality of real-world video content. This paper proposes a hybrid model to address this problem. Both a generic AAM and a subject-specific model are employed simultaneously in the proposed fitting scheme. Experimental results from outdoor surveillance video sequences demonstrate the improved image registration across video frames and faster fitting convergence.

关键词： Video recording

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Face model fitting on low resolution images

Face model fitting on low resolution images

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2006 17th British Machine vision Conference, BMVC 2006

作者： Liu, Xiaoming Tu, Peter H. Wheeler, Frederick W. Visualization and Computer Vision Lab. General Electric Global Research Center Niskayuna NY 12309 United States

ISBN: (纸本)1904410146

Active Appearance Models (AAMs) represent the shape and appearance of an object via two low-dimensional subspaces, one for shape and one for appearance. AAMs for facial images are currently receiving considerable attention from the vision community. However, most existing work focuses on fitting AAMs to high-quality facial images. For many applications, effectively fitting an AAM to low-resolution facial images is of critical importance. This paper addresses this challenge from two aspects. On the modeling side, we propose an iterative AAM enhancement scheme, which not only results in increased fitting speed, but also improves the fitting robustness. For fitting AAMs to low-resolution images, we build a multi-resolution AAM and show that the best fitting performance is obtained when the model resolution is slightly higher than the facial image resolution. Experimental results using both indoor video and outdoor surveillance video are presented.

关键词： Image resolution

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Age range estimation based on facial wrinkle analysis using hessian based filter 2nd

Age range estimation based on facial wrinkle analysis using ...

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2nd International Conference on Communication and computer Engineering, ICOCOE 2015

作者： Razalli, Husniza Rahmat, Rahmita Wirza O. K. Khalid, Fatimah Sulaiman, Puteri Suhaiza Signal Processing Lab TM Research and Development Cyberjaya Selangor Malaysia Computer Graphics Vision and Visualization Research Group Universiti Putra Malaysia Serdang Selangor Malaysia

ISBN: (纸本)9783319245829

Aging is a normal process that has an effect on different parts of the human body under the influence of various biological and environmental aspects. The most prominent changes that occur on the face are the form of the skin wrinkles, which are the main objective of this research. Specific wrinkle detection is an important task in face textural analysis. Previously, some researchers have been proposed the age range estimation based on wrinkle analysis in literature, but poor localization limits the performance of the whole age estimation process. This is because, when less number of wrinkles are detected or extracted, it will consequently affect the process to estimate the correct age. Therefore, we address this issue to enhance age range estimation method using a new approach to extract correct facial wrinkles for further analysis. We propose a method to extract facial wrinkle in face image using Hessian based filter (HBF) for age estimation. In other word, this research focus on age range estimation method based on facial wrinkle analysis extracted from facial image obtained from FG-NET database using hessian based filter. The proposed filter is theoretically straightforward, however, it significantly increases the wrinkle analysis result compared to previous methods. The result shows that HBF successfully obtained higher accuracy with over 90 % estimation rate. © Springer International Publishing Switzerland 2016.

关键词： Bandpass filters

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Optimal pose for face recognition

Optimal pose for face recognition

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2006 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2006

作者： Liu, Xiaoming Chen, Tsuhan Rittscher, Jens Visualization and Computer Vision Lab. General Electric Global Research Center Schenectady NY 12309 Advanced Multimedia Processing Lab. Carnegie Mellon University Pittsburgh PA 15213

ISBN: (纸本)0769525970

Researchers in psychology have well studied the impact of the pose of a face as perceived by humans, and concluded that the so-called 3/4 view, halfway between the front view and the profile view, is the easiest for face recognition by humans. For face recognition by machines, while much work has been done to create recognition algorithms that are robust to pose variation, little has been done in finding the most representative pose for recognition. In this paper, we use a number of algorithms to evaluate face recognition performance when various poses are used for training. The result, similar to findings in psychology that the 3/4 view is the best, is also justified by the discrimination power of different regions on the face, computed from both the appearance and the geometry of these regions. We believe our study is both scientifically interesting and practically beneficial for many applications. © 2006 IEEE.

关键词： Face recognition

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OpenKG Chain:A Blockchain Infrastructure for Open Knowledge Graphs

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Data Intelligence 2021年第2期3卷 205-227页

作者： Huajun Chen Ning Hu Guilin Qi Haofen Wang Zhen Bi Jie Li Fan Yang College of Computer Science&AZFT Knowledge Engine Lab Zhejiang UniversityHangzhou 310058China Ontology Foundation Venture Drive#11-31Vision ExchangeSingapore 608526Singapore School of Computer Science and Engineering Southeast UniversityNanjing 211189China Intelligent Big Data Visualization Lab Tongji UniversityShanghai 200092China

The early concept of knowledge graph originates from the idea of the semantic Web,which aims at using structured graphs to model the knowledge of the world and record the relationships that exist between *** publishing knowledge bases as open data on the Web has gained significant *** China,Chinese Information Processing Society of China(CIPS)launched the OpenKG in 2015 to foster the development of Chinese Open Knowledge *** existing open knowledge-based programs,OpenKG chain is envisioned as a blockchain-based open knowledge *** article introduces the first attempt at the implementation of sharing knowledge graphs on OpenKG chain,a blockchain-based trust *** have completed the test of the underlying blockchain platform,and the on-chain test of OpenKG’s data set and tool set sharing as well as fine-grained knowledge crowdsourcing at the triple *** have also proposed novel definitions:K-Point and OpenKG Token,which can be considered to be a measurement of knowledge value and user value.1,033 knowledge contributors have been involved in two months of testing on the blockchain,and the cumulative number of on-chain recordings triggered by real knowledge consumers has reached 550,000 with an average daily peak value of more than 10,*** the first time,we have tested and realized on-chain sharing of knowledge at entity/triple granularity *** present,all operations on the data sets and tool sets at ***,as well as the triplets at OpenBase,are recorded on the chain,and corresponding value will also be generated and assigned in a trusted *** this effort,OpenKG chain looks forward to providing a more credible and traceable knowledge-sharing platform for the knowledge graph community.

关键词： Open knowledge graph Blockchain Decentralized distributed network Decentralized knowledge graph

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Region moments: Fast invariant descriptors for detecting small image structures

Region moments: Fast invariant descriptors for detecting sma...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Gianfranco Doretto Yi Yao Visualization and Computer Vision Lab GE Global Research Center Niskayuna NY USA

This paper presents region moments, a class of appearance descriptors based on image moments applied to a pool of image features. A careful design of the moments and the image features, makes the descriptors scale and rotation invariant, and therefore suitable for vehicle detection from aerial video, where targets appear at different scales and orientations. Region moments are linearly related to the image features. Thus, comparing descriptors by computing costly geodesic distances and non-linear classifiers can be avoided, because Euclidean geometry and linear classifiers are still effective. The descriptor computation is made efficient by designing a fast procedure based on the integral representation. An extensive comparison between region moments and the region covariance descriptors, reports theoretical, qualitative, and quantitative differences among them, with a clear advantage of the region moments, when used for detecting small image structures, such as vehicles in aerial video. The proposed descriptors hold the promise to become an effective building block in other applications.

关键词： Vehicle detection Geophysics computing Vehicles visualization computer vision Computational geometry computer applications Object detection Image recognition Noise robustness

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