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A DATASET FOR SCENE CLASSIFICATION BASED ON CAMERA METADATA

A DATASET FOR SCENE CLASSIFICATION BASED ON CAMERA METADATA

The 3rd IEEE International Conference on Network Infrastructure and Digital Content (2012年第三届IEEE网络基础设施与数字内容国际会议(IEEE IC-NIDC2012))

作者： Honggang Zhang Can Cao Kaili Zhao Yizhe Song Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunicat School of Electronic Engineering and Computer Science Queen Mary University of London UK

In this paper,we introduce a new dataset for scene classification based on camera *** classify the most common scenes that have been researched much *** dataset consists of 12 scene *** category contains 500 to 2000 *** images are high resolution such as 2000x2000 *** images in the dataset are original,namely,each image brings with a camera metadata (EXIF).Various types,metadata cues of photos,strict definitions among scenes are characteristic factors that make this dataset a very challenging testbed for photo *** supply the scene photos together with scene labeling,as well as the EXIF information extraction via methodology,and we apply the dataset into sementic scene classification up to now.

关键词： Scene classification Camera metadata EXIF

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Efficient a priori SNR estimation based on parameter adaptive spectral method

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Journal of China Universities of Posts and Telecommunications 2011年第SUPPL. 1期18卷 60-63页

作者： Fang, Yu Liu, Gang Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

The a priori signal-to-noise (SNR) is one of the most important parameters in the short-time spectrum estimation techniques in speech enhancement. A new and convenient algorithm to estimate the priori SNR is involved in this paper. In this paper, the priori and posterior SNR of intra-frame are defined which can trace the variation of the a priori SNR of each frame better and can solve the problem of delay involved by the traditional approaches. Simulation shows that, the performance of the proposed algorithm is better than the traditional estimators in terms of log-spectral distance and the improvement segmental SNR, especially in the no stationary noise environments. © 2011 The Journal of China Universities of Posts and Telecommunications.

关键词： Speech enhancement

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Speech enhancement based on modified a priori SNR estimation

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Frontiers of Electrical and Electronic Engineering in China 2011年第4期6卷 542-546页

作者： Yu FANG Gang LIU Jun GUO Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and TelecommunicationsBeijing 100876China

To solve the frame delay problem and match the previous frame,Plapous et al.[IEEE Transactions on Audio,Speech,and Language Processing,2006,14(6):2098–2108]introduced a novel approach called two-step noise reduction(TSNR)technique to improve the performance of the speech enhancement ***,TSNR approach results in spectral peaks of short duration and the broken spectral outlier,which degrade the spectral characteristics of the *** solve this problem,a cepstral smoothing step is added in order to remove these spectral peaks brought by TSNR *** analysis shows that the proposed approach can effectively smooth the spectral peaks and keep the spectral outlier so as to protect the speech *** results also show that the proposed approach can bring significant improvement compared to decision-directed(DD)and TSNR approaches,especially in non-stationary noisy environments.

关键词： speech enhancement decision-directed(DD) two-step noise reduction(TSNR) signal-to-noise ratio(SNR)estimation

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Lower bounds on some van der waerden numbers based on quadratic residues

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Journal of Combinatorial Mathematics and Combinatorial Computing 2012年 83卷 23-31页

作者： Liang, Meilian Xu, Xiaodong Shao, Zehui Xiu, Baoxin School of Mathematics and Information Science Guangxi University Nanning 530004 China Guangxi Academy of Sciences Nanning 530007 China Key Laboratory of Pattern Recognition and Intelligent Information Processing School of Information Science and Technology Chengdu University Chengdu 610106 China College of Information System and Management National University of Defense Technology Changsha 410073 China

The van der Waerden number W(r, k) is the least integer N such that every r-coloring of {1,2, • • •, N} contains a monochromatic arithmetic progression of length at least k. Rabung gave a method to obtain lower bounds on W(2,k) based on quadratic residues, and performed computations on all primes no greater than 20117. By improving the efficiency of the algorithm of Rabung, we perform the computation for all primes up to 6 x 107, and obtain lower bounds on W(2, k) for k between 11 and 23.

关键词： Computational efficiency

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Voice-based local search using a language model look-ahead structure for efficient pruning

Voice-based local search using a language model look-ahead s...

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2011 7th International Conference on Computational Intelligence and Security, CIS 2011

作者： Lu, Yao Liu, Gang Chen, Wei Olsen, Jesper Pattern Recognition and Intelligent System Laboratory BUPT Beijing China Nokia Research Center NOKIA Beijing China

ISBN: (纸本)9780769545844

On mobile terminals, voice-based local search services [1] are quickly becoming a new important application. Voice search is essentially a large vocabulary speech recognition task with an open ended vocabulary, and this is a problem because speed and accuracy are essential for a good user experience. Fortunately when a user submits a local search query, contextual information such as the user's current position can be used for constraining the full search space. In this paper, we use local information and present a pruning algorithm based on a LMLA (Language Model Look-Ahead) tree, which can significantly improve both the speed and the accuracy of the voice search system. © 2011 IEEE.

关键词： Trees (mathematics)

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Clustering-based Discriminative Locality Alignment for Face Gender recognition

Clustering-based Discriminative Locality Alignment for Face ...

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IEEE/RSJ International Conference on intelligent Robotics and systems

作者： Duo Chen Jun Cheng Dacheng Tao College of Communication Engineering Chongqing University Chongqing 400044 China. He is also with the Shenzhen Key Laboratory of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences. Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. He is also with the Chinese University of Hong Kong and Guangdong Provincial Key Laboratory of Robotics and Intelligent System. Center for Quantum Computation and Intelligent System Faculty of Engineering and Information Technology University of Technology Sydney New South Wales 2007 Australia.

ISBN: (数字)9781467317368

ISBN: (纸本)9781467317375

To facilitate human-robot interactions, human gender information is very important. Motivated by the success of manifold learning for visual recognition, we present a novel clustering-based discriminative locality alignment (CDLA) algorithm to discover the low-dimensional intrinsic submanifold from the embedding high-dimensional ambient space for improving the face gender recognition performance. In particular, CDLA exploits the global geometry through k-means clustering, extracts the discriminative information through margin maximization and explores the local geometry through intra cluster sample concentration. These three properties uniquely characterize CDLA for face gender recognition. The experimental results obtained from the FERET data sets suggest the superiority of the proposed method in terms of recognition speed and accuracy by comparing with several representative methods.

关键词： FERET CDLA comparing recognition (Psychology) Gender Global geometry Compare Face Face

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Misclassification and margin based SVM active learning algorithm for audio event detection

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International Journal of Advancements in Computing Technology 2011年第9期3卷 90-97页

作者： Leng, Yan Liu, Gang Qi, Guanghui Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China College of Physics and Electronics Shandong Normal University Jinan 250014 China Department of Construction Machinery Shandong Jiaotong University Jinan 250023 China

Audio event detection has become a hot research due to its wide applications in many fields, such as multimedia retrieval etc., the detection needs large amounts of labeled samples to train the audio event models, but in real life, the labeled samples are expensive to obtain, the shortage of such labeled samples is a big obstacle. Active learning is an efficient way to deal with the problem of insufficient labeled samples. The most popular support vector machines active learning is the margin based sampling (MBS), which is to query the sample closest to the current hyperplane, but when the current hyperplane is far away from the true hyperplane, the sample closest to the current hyperplane is not so informative, querying such samples would have a much slower adjustment of the hyperplane. In order to accelerate the adjustment, this paper proposes the misclassification and margin based sampling (MMBS) active learning algorithm. In order to query more informative samples, MMBS selects samples based on misclassified samples' KL divergence in the first few iterations, after that, considering the lower misclassification confidence and the outlier problem, it switches to MBS. Experiments show that compared to MBS and representative sampling (RepS), MMBS can get the highest detection performance under the same human annotation workload.

关键词： Support vector machines

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A novel keypoint detection in wavelet pyramid space

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第6期5卷 55-62页

作者： Gao, Yanyan Zhang, Honggang Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and telecommunications Beijing China

Keypoint detection is important for object recognition, image retrieval, mosaicing etc., and has attracted ample research. In this paper, we propose a novel wavelet-based detector (NWBD) based on the previous researches on keypoint detection. NWBD is performed in wavelet pyramid space, it extracts the local extrema of the energy map computed by intra-scale coefficient product (ISCP) as the candidate keypoint, and then discards some points by Hessian matrix. In the experiments, the novel detector was compared with Harris detector and SIFT detector by the evaluation of repeatability, and it achieved better performance for some scenes in the database provided by Mikolajcyzk and Schmid, such as wall, trees, and graffiti.

关键词： Object recognition

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Multi-feature content-based product image retrieval based on region of main object

Multi-feature content-based product image retrieval based on...

引用

8th International Conference on Information, Communications and Signal Processing, ICICS 2011

作者： Chai, Lunshao Zhang, Honggang Qin, Zhen Yu, Jie Qi, Yonggang Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Riverside Lab for Artificial Intelligence Research University of California Riverside Riverside CA United States

ISBN: (纸本)9781457700309

Content-based image retrieval (CBIR) has got an intense interest and seen considerable progress over the last decade. But most of the time it is only applied in laboratory. One important reason for this is the diversity of images. Different practical situations call for different taxonomy definitions of images, and lead to very different solutions. At present, and even in the foreseeable future, a general purpose CBIR system is not really possible. However, image search engines oriented at specific domains are feasible in technology and also have the actual demand. With the rapid development of electronic commerce, searching specific product by image has become one of the most attractive related research topics. In this paper, we propose a region-based method fit for the content-based retrieval of product images. The method focuses on two key issues: fast extraction of the main region, in which the product locates, as well as efficient shape and color features extraction. To show the validity of the proposed region-based method, compared experiments are carried out and illustrated on the PI 100 dataset. © 2011 IEEE.

关键词： Content based retrieval

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Tweets Reading Probability Analysis Based on Competing-Window Model

Tweets Reading Probability Analysis Based on Competing-Windo...

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International Conference on Intelligence Science and Information Engineering (ISIE)

作者： Jianjun Xie Chuang Zhang Ming Wu Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

In microgblogs, a user usually follows or is followed by many other users. The content updating and reading is a complex process involving intensive interactions among publishers and readers. It also forms the basis of information diffusion in social networks. In the situation of massive followers, tweets reading would heavily depend on user behaviors and interactions. The tweets reading probability (TRP) would be a vital parameter measuring the effectiveness and influence of tweets. Our work proposed a fundamental model, namely competing-window, to simulate the process of multi-node interactions and analyzed TRP in social network. Based on Sina Microblog, we built a standard data set and run massive experiments on empirical data to extract user behavior patterns. By adopting simulating approaches, TRP in a none-preference social network was obtained. The results indicate that typical TRP is about 8% and different user behaviors affect TRP differently.

关键词： Data mining Publishing Conferences Twitter Data models Analytical models

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