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International Conference on Information and Automation (ICIA)

作者： Yuanrong Xu Qianqian Wang Xiao Bai Yen-Lun Chen Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences University of Science and Technology of China Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the variation of orientation angles, and the other criterion is the order of the appearance of features. Experimental results show that this method can classify the dynamic hand gestures effectively.

关键词： Vectors Trajectory Feature extraction Equations Mathematical model Hidden Markov models Automation

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Dynamic hand gesture early recognition based on Hidden Semi-Markov Models

Dynamic hand gesture early recognition based on Hidden Semi-...

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IEEE International Conference on Robotics and Biomimetics

作者： Qianqian Wang Yuanrong Xu Yen-Lun Chen Yong Wang Xinyu Wu University of Science and Technology of China Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong. Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

ISBN: (纸本)9781479973989

Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on the dataset which we established demonstrate the effectiveness of our method.

关键词： Hidden Markov models Gesture recognition Training Conferences Trajectory Arrays

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Graph Embedding Based Semi-supervised Discriminative Tracker

Graph Embedding Based Semi-supervised Discriminative Tracker

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Jin Gao Junliang Xing Weiming Hu Xiaoqin Zhang National Laboratory of Pattern Recognition Institute of Automation China Institute of Intelligent System and Decision Wenzhou University China

Recently, constructing a good graph to represent data structures is widely used in machine learning based applications. Some existing trackers have adopted graph construction based classifiers for tracking. However, their graph structures are not effective to characterize the inter-class separability and multi-model sample distribution, both of which are very important to successful tracking. In this paper, we propose to use a new graph structure to improve tracking performance without the assistance of learning object subspace generatively as previous work did. Meanwhile, considering the test samples deviate from the distribution of the training samples in tracking applications, we formulate the discriminative learning process, to avoid over fitting, in a semi-supervised fashion as L1-graph based regularizer. In addition, a non-linear variant is extended to adapt to multi-modal sample distribution. Experimental results demonstrate the superior properties of the proposed tracker.

关键词： Vectors Training Feature extraction Hilbert space Robustness Noise Covariance matrices

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Rapid disparity prediction for dynamic scenes

Rapid disparity prediction for dynamic scenes

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9th International Symposium on Advances in Visual Computing, ISVC 2013

作者： Jiang, Jun Cheng, Jun Chen, Baowen Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Chinese University of Hong Kong Hong Kong Hong Kong Shsenzhen Institute of Information Technology China Guangdong Provincial Key Laboratory of Robotics and Intelligent System China Shenzhen Key Laboratory of Computer Vision and Pattern Recognition China

ISBN: (纸本)9783642419133

Real-time 3D sensing plays a critical role in robotic navigation, video surveillance and human-computer interaction, etc. When computing 3D structures of dynamic scenes from stereo sequences, spatiotemporal stereo and scene flow methods can produce temporally coherent disparity. However, most existing methods do not utilize the previous disparity map sufficiently to compute the next disparity map, and the searching space of correspondences limits the speed of disparity computation for each image pair. This paper proposes an effective scheme to predict disparity maps from stereo sequences. In particular, we apply a robust 3D registration algorithm based on the angular-invariant feature to estimate the ego-motion of the stereo rig between consecutive frames, and present the transformation between consecutive disparity maps. The scheme can produce a sequence of temporally coherent disparity maps rapidly. We apply the new scheme to real outdoor scenes, and thorough empirical studies indicate the effectiveness of the new scheme for practical applications. © 2013 Springer-Verlag.

关键词： Human computer interaction

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REPRESENTATIVE REFERENCE-SET AND BETWEENNESS CENTRALITY FOR SCENE IMAGE CATEGORIZATION

REPRESENTATIVE REFERENCE-SET AND BETWEENNESS CENTRALITY FOR ...

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IEEE International Conference on Image Processing

作者： Qun Li Zhen Qin Lunshao Chai Honggang Zhang Jim Guo Bir Bhanu Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China University of California Riverside CA USA

ISBN: (纸本)9781479923427

Reference-based image classification approach introduces a reference-set for both image representation and dictionary learning. It significantly reduces the dimensionality of represented images and shows outstanding performance even with randomly selected reference images and simple distance measure. In this paper, we improve upon existing work with two major contributions. First, we show that a more representative reference-set contributes to better classification accuracy. To this end, we carefully adapt the K-means clustering algorithm in the feature space to select a distinguished reference-set. Second, in the image classification process, we propose to represent each image by measuring its betweenness centrality in a social network composed of the representative reference-set in each class, leading to a more coherent distance measure that considers the overall connectivity between the probe image and the reference-set. Extensive experiment results demonstrate that our proposed scheme achieves better performance than existing methods.

关键词： Scene categorization reference-based scheme K-means social network betweenness Social Media Social Networks images Image classification distance measurement Eigenvector image representation Imagery (Psychotherapy)

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Audio Fingerprinting Based on N-grams

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第10期6卷 361-368页

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

In this paper, we present a novel audio fingerprinting method based on N-grams, which can quickly identify a segment of audio even when the audio signals are seriously distorted. We make use of N peaks in spectrum to form the audio fingerprint, which accelerates the retrieval speed greatly. We take advantage of the initial robust peaks to calculate the similarity between candidates and the input audio, which improves the retrieval accuracy significantly. The effectiveness of the N-gram method was evaluated on a music database of 10,000 songs. Experimental results show that the proposed approach outperforms two state-of-the-art algorithms (Shazam and Philips Robust Hash) in both effectiveness (in terms of retrieval accuracy) and efficiency (in terms of average retrieval time).

关键词： Music

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Sparse feature representation for visual tracking

Sparse feature representation for visual tracking

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2012 International Conference on systems and Informatics, ICSAI 2012

作者： Liu, Yifei Han, Zhenjun Ye, Qixiang Jiao, Jianbin Li, Ce Pattern Recognition and Intelligent System Development Laboratory Graduate University Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467301992

In this paper, a novel sparse feature representation method for object tracking is proposed. The method is on the observation that a tracked object can be dynamically and compactly represented by a few features (sparse representation) from a large feature set (the improved histogram of oriented gradient and color, HOGC). Based on the HOGC features, the sparse representation can be learned online from the constructed training samples during the tracking procedure by exploiting the L1-norm minimization principle, which can also be called feature selection procedure, ensuring the tracking can adapt to the appearance variations of either foreground or background. Experiments with comparisons demonstrate the effectiveness of the proposed method. © 2012 IEEE.

关键词： Feature Selection

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Tempo Variation Based Multilayer Filters for Query by Humming

Tempo Variation Based Multilayer Filters for Query by Hummin...

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International Conference on pattern recognition

作者： Qiang Wang Zhiyuan Guo Baoxiang Li Gang Liu Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications

ISBN: (纸本)9781467322164

In this paper we propose a methodology of multilayer filters based on tempo variation for realizing a query by humming (QBH) system. Firstly the original query clip is used to search for the candidate songs. If the results are unreliable, the clip is linearly scaled twice for more candidates. If the results are still unreliable, the clip is scaled more times for retrieval. To sort all the candidates, a new matching algorithm called key transposition recursive alignment (KTRA) is presented, which improves the retrieval accuracy. Experimental results on the 2010 MIREX QBH query corpus show that the proposed method can achieve a relative improvement of 20.9% as well as an acceleration factor of 2.09 simultaneously compared to a state-of-the-art method.

关键词： music query processing

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WAF BASED TOPIC DETECTION IN MICRO-BLOG

WAF BASED TOPIC DETECTION IN MICRO-BLOG

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2012 IEEE 2nd International Conference on Cloud Computing and Intelligence systems

作者： Xiaoning Li Guang Chen Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications

Micro-blog is a new information sharing tool which is more and more popular these days. In very short time there are a large number of messages posted and it is difficult for people to grasp main topics that most people are talking about. In this paper, we introduce a new text modeling method, which is called WAF, and propose a feature selection method for topic clustering based on it. In the experiments this method shows promising results, and the subsequent clustering based on it works effectively as well.

关键词： Micro-blog topic detection WAF Clustering

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A music retrieval system based on spoken lyric queries

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International Journal of Advancements in Computing Technology 2012年第8期4卷 173-180页

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

This paper proposes a spoken lyric search system, which can help users to find the wanted music based on their input spoken lyric phrases. Using spoken lyric phrases to query a music retrieval system is convenient for users but challenging for developers. In our proposed system, the spoken query will be converted into text using large vocabulary continuous speech recognition (LVCSR) technique at first, and then a list of candidate lyrics and their corresponding songs will be presented by the text retrieval techniques. To guarantee the performance of the system, we propose a novel approach to improving the current technology. Specifically, a string matching method, which is based on phoneme confusion matrix, is applied to search the most similar lyrics in acoustic respect for the multiple sentence hypotheses of the input voice;and a two-level search strategy is adopted to shorten the time consuming. Experimental results show that the proposed system achieved top-1 accuracy as high as 93.98% when the search is performed within 2,000 songs, and 83.20%, a moderately satisfying accuracy, was obtained when the targeted number of songs increased to 10,000.

关键词： Character recognition

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