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International Conference on image and Graphics

作者： Wang, Jiewei Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing Beihang University Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9780769545417

Compared with traditional video summarization approaches, aerial video summarization is a new and challenging issue for its particular characteristics. Aerial video data is a massive data stream, without pre-edit structures such as sports or news video data, lack of camera motion such as zoom and pan. On account of these characteristics, we proposed a novel approach for summarization. First, we extract GIST features for each frame as the holistic scene representation. Then, we divide aerial video into temporal segments representing a visual scene using on-line clustering method by examine GIST features of each frame only once. Finally, we select several key frames from each scene for summarization according to visual saliency index (VSI) of each frame computed from their visual saliency map. In the paper, we proposed new criterion for estimation of temporal segmentation of streaming video. Experimental observations show the success of our approach on aerial video summarization. © 2011 IEEE.

关键词： Antennas

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A fast rich information-based stereo matching framework

A fast rich information-based stereo matching framework

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2009 Chinese Conference on Pattern recognition, CCPR 2009 and the 1st CJK Joint Workshop on Pattern recognition, CJKPR

作者： Yuhang, Zhao Junge, Sun Xiao, Bai Yunhong, Wang Intelligence Recognition and Image Processing Lab School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781424441990

With the recent development on image affine region descriptors, we can extract more salient and useful local information from images. That information can be used to help us to better solve a fundamental problem in computer vision - stereo vision. In this paper we propose a framework for stereo matching problems in order to give a rich-information based, high-precision and fast solution. Affine regions based SIFT are chosen as features rather than point features to extract more information. In the matching period, a search algorithm with incremental dissimilarity approximations is used for efficient computing. For correctness, MLESAC(Maximum Likelihood Estimation Sample Consensus) method is used to eliminate outliers. In the experiment part, we evaluate different combinations on the performance of speed, correctness and transformations. ©2009 IEEE.

关键词： Maximum likelihood estimation

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Learning group interaction for sports video understanding from a perspective of athlete

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Frontiers of Computer Science 2024年第4期18卷 175-188页

作者： Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN Intelligent Recognition and Image Processing(IRIP)Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Hangzhou Innovation Institute Behang UniversityHangzhou 310051China National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT or CNCERT/CC) Beijing 100029China

Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation Network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional Networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关键词： group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding

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image processing On-Board Small Remote Sensing Satellites

Image Processing On-Board Small Remote Sensing Satellites

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2010 4th International Conference on intelligent Information Technology Application (IITA2010)

作者： Roberto Arenas Lara Lab of Intelligent Recognition and Image Processing Beihang University

Current Remote Sensing space missions have very restricted image processing capabilities on-board,and also the improvement of the down-link on Earth Observation Satellites is a topic on the table,mostly because of the amount of data generated by the sensors,the short time to download of the images from the satellites and the limited bandwidth *** overview of recent remote sensing missions and the motivations that must guide these studies are presented in this paper.

关键词： image processing remote sensing on-board small satellites

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BUAA-iCC at imageCLEF 2015 scalable concept image annotation challenge 16

BUAA-iCC at ImageCLEF 2015 scalable concept image annotation...

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16th Conference and labs of the Evaluation Forum, CLEF 2015

作者： Wang, Yunhong Chen, Jiaxin Liu, Ningning Zhang, Li Intelligent Recognition and Image Processing Lab Beihang University Beijing100191 China School of Information Technology and Management University of International Business and Economics Beijing100029 China

In this working note, we mainly focus on the image annotation subtask of imageCLEF 2015 challenge that BUAA-iCC research group participated. For this task, we firstly explore textual similarity information between each test sample and predefined concept. Subsequently, two different kinds of semantic information are extracted from visual images: visual tags using generic object recognition classifiers and visual tags relevant to human being related concepts. For the former information, the visual tags are predicted by using deep convolutional neural network (CNN) and a set of support vector machines trained on imageNet, and finally transferred to textual information. For the latter visual information, human related concepts are extracted via face and facial attribute detection, and finally transferred to similarity information by using manually designed mapping rules, in order to enhance the performance of annotating human related concepts. Meanwhile, a late fusion strategy is developed to incorporate aforementioned various kinds of similarity information. Results validate that the combination of the textual and visual similarity information and the adopted late fusion strategy could yield significantly better performance.

关键词： image annotation

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Investigating the separability of features from different views for gait based gender classification

Investigating the separability of features from different vi...

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作者： Zhang, De Wang, Yunhong Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781424421756

In this paper, we investigate the efficiency of different view angles when classifying gender with gait biometrics for the first time. A gait database is built for this purpose in which walking videos are recorded at seven different views for each subject. Then, we employ a robust gait representation method to extract gait features. The class separability of these features from different view angles are analyzed and compared. A set of experiments are designed to evaluate the performance of gait based gender classification along with the changes of view angle. The experimental results show that 0° and 180° are the worst view angles in this two-category case and the 90° view dose not perform the best, unlike it takes the best performance in gait recognition. © 2008 IEEE.

关键词： Pattern recognition

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Ethnicity classification based on gait using multi-view fusion

Ethnicity classification based on gait using multi-view fusi...

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2010 IEEE Computer Society Conference on Computer Vision and Pattern recognition - Workshops, CVPRW 2010

作者： Zhang, De Wang, Yunhong Bhanu, Bir Intelligent Recognition and Image Processing Laboratory Beihang University Beijing 100191 China Center for Research in Intelligent Systems University of California Riverside CA 92521 United States

ISBN: (纸本)9781424470297

The determination of ethnicity of an individual, as a soft biometrics, can be very useful in a video-based surveillance system. Currently, face is commonly used to determine the ethnicity of a person. Up to now, gait has been used for individual recognition and gender classification but not for ethnicity determination. This paper focuses on the ethnicity determination based on fusion of multi-view gait. Gait Energy image (GEI) is used to analyze the recognition power of gait for ethnicity. Feature fusion, score fusion and decision fusion from multiple views of gait are explored. For the feature fusion, GEI images and camera views are put together to render a third-order tensor (x;y;view). A multilinear principal component analysis (MPCA) is used to extract features from tensor objects which integrate all views. For the score fusion, the similarity scores measured from single views are combined with a weighted SUM rule. For the decision fusion, ethnicity classification is realized on each individual view first. The classification results are then combined to make the final determination with a majority vote rule. A database of 36 walking people (East Asian and South American) was acquired from 7 different camera views. The experimental results show that ethnicity can be determined from human gait in video automatically. The classification rate is improved by fusing multiple camera views and a comparison among different fusion schemes shows that the MPCA based feature fusion performs thebest. © 2010 IEEE.

关键词： Principal component analysis

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Biometric information hiding: Promoting multimedia security with content and identity authentication

Biometric information hiding: Promoting multimedia security ...

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2013 IEEE China Summit and International Conference on Signal and Information processing, ChinaSIP 2013

作者： Ma, Bin Li, Chunlei Zhang, Zhaoxiang Wang, Yunhong Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China School of Electronic and Information Engineering Zhongyuan University of Technology Zhengzhou China

ISBN: (纸本)9781479910434

Biometrics and information hiding, as two different yet promising techniques for individual identification and digital media protection, have been extensively studied in the latest decade. Recently, hybrid approaches that combine these two techniques (i.e., biometric information hiding) for advanced information security have obtained increasing research interest. The principle idea is applying information hiding as data anti-counterfeit tool for secure biometric authentication, or introducing biometrics as identity token to information hiding applications such as: owner identification, traitor tracing. In this paper, we present a brief classification of existing biometric information hiding approaches and discuss the corresponding emerged requirements. Meanwhile, two typical application cases proposed in our previous work, which adopted face and fingerprint as watermarks respectively are further discussed and analysed. © 2013 IEEE.

关键词： Biometrics

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Age classification based on gait using HMM

Age classification based on gait using HMM

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2010 20th International Conference on Pattern recognition, ICPR 2010

作者： Zhang, De Wang, Yunhong Bhanu, Bir Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100191 China Center for Research in Intelligent Systems University of California Riverside CA 92521 United States

ISBN: (纸本)9780769541099

In this paper we propose a new framework for age classification based on human gait using Hidden Markov Model (HMM). A gait database including young people and elderly people is built. To extract appropriate gait features, we consider a contour related method in terms of shape variations during human walking. Then the image feature is transformed to a lower-dimensional space by using the Frame to Exemplar (FED) distance. A HMM is trained on the FED vector sequences. Thus, the framework provides flexibility in the selection of gait feature representation. In addition, the framework is robust for classification due to the statistical nature of HMM. The experimental results show that video-based automatic age classification from human gait is feasible and reliable. © 2010 IEEE.

关键词： Hidden Markov models

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Lossless Compression On-Board Remote Sensing Satellites

Lossless Compression On-Board Remote Sensing Satellites

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2011 International Conference on Future Computer Science and Education（ICFCSE 2011）

作者： Roberto Arenas Lara Yunhong Wang Lab of Intelligent Recognition and Image Processing Beihang University School of Computer Science and Engineering Beihang University

image processing on-board satellites is no longer a nice to have feature. Lossless image compression allows increasing the stored data on-board satellite and transmitting it to the ground station without losing quality of the images. An overview of development trend in this area, as well as brief state-of-the-art lossless image compression methods on-board satellites are presented in this paper.

关键词： Lossless compression image processing on-board satellite remote sensing

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