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Tracking benchmark databases for video-based sign language recognition

Tracking benchmark databases for video-based sign language r...

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11th European conference on computer vision, ECCV 2010

作者： Dreuw, Philippe Forster, Jens Ney, Hermann Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen Germany

A survey of video databases that can be used within a continuous sign language recognition scenario to measure the performance of head and hand tracking algorithms either w.r.t. a tracking error rate or w.r.t. a word error rate criterion is presented in this work. Robust tracking algorithms are required as the signing hand frequently moves in front of the face, may temporarily disappear, or cross the other hand. Only few studies consider the recognition of continuous sign language, and usually special devices such as colored gloves or blue-boxing environments are used to accurately track the regions-of-interest in sign language processing. Ground-truth labels for hand and head positions have been annotated for more than 30k frames in several publicly available video databases of different degrees of difficulty, and preliminary tracking results are presented. © 2012 Springer-Verlag.

关键词： Database systems

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Isometric multi-manifold learning for feature extraction

Isometric multi-manifold learning for feature extraction

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12th IEEE International conference on Data Mining (ICDM)

作者： Fan, Mingyu Qiao, Hong Zhang, Bo Zhang, Xiaoqin Wenzhou Univ Inst Intelligent Syst & Decis Wenzhou Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China Chinese Acad Sci Inst Appl Math Beijing Peoples R China

ISBN: (纸本)9781467346498;9780769549057

Manifold learning is an important topic in pattern recognition and computer vision. However, most manifold learning algorithms implicitly assume the data are aligned on a single manifold, which is too strict in actual applications. Isometric feature mapping (Isomap), as a promising manifold learning method, fails to work on data which distribute on clusters in a single manifold or manifolds. In this paper, we propose a new multi-manifold learning algorithm (M-Isomap). the algorithm first discovers the data manifolds and then reduces the dimensionality of the manifolds separately. Meanwhile, a skeleton representing the global structure of whole data set is built and kept in low-dimensional space. Secondly, by referring to the low-dimensional representation of the skeleton, the embeddings of the manifolds are relocated to a global coordinate system. Compared with previous methods, these algorithms can keep both of the intra and inter manifolds geodesics faithfully. the features and effectiveness of the proposed multi-manifold learning algorithms are demonstrated and compared through experiments.

关键词： Feature extraction multi-manifold learning geodesic distance

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Detecting People Carrying Objects utilizing Lagrangian Dynamics

Detecting People Carrying Objects utilizing Lagrangian Dynam...

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9th IEEE International conference on Advanced Video and Signal-Based Surveillance (AVSS)

作者： Senst, Tobias Kuhn, Alexander theisel, Holger Sikora, thomas Tech Univ Berlin Commun Syst Grp Berlin Germany Univ Magdeburg Visual Comp Grp Magdeburg Germany

ISBN: (纸本)9780769547978

the availability of dense motion information in computer vision domain allows for the effective application of Lagrangian techniques that have their origin in fluid flow analysis and dynamical systems theory. A well established technique that has been proven to be useful in image-based crowd analysis are Finite Time Lyapunov Exponents (FTLE). Based on this, we present a method to detect people carrying object and describe a methodology how to apply established flow field methods onto the problem of describing individuals. Further, we reinterpret Lagrangian features in relation to the underlying motion process and show their applicability towards the appearance modeling of pedestrians. this definition allows to increase performance of state-of-the-art methods and is shown to be robust under varying parameter settings and different optical flow extraction approaches.

关键词： people carrying objects motion descriptor lagrangian dynamics optical flow FTLE HOG

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Online non-feedback image re-ranking via dominant data selection

Online non-feedback image re-ranking via dominant data selec...

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20th ACM International conference on Multimedia, MM 2012

作者： Cao, Chen Chen, Shifeng Li, Yuhong Liu, Jianzhuang Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Information Engineering Chinese University of Hong Kong Hong Kong Media Lab. Huawei Technologies Co. Ltd. China

ISBN: (纸本)9781450310895

Image re-ranking aims at improving the precision of keyword-based image retrieval, mainly by introducing visual features to re-rank. Many existing approaches require offline training for every keyword, which are unsuitable for online image search. Other real-time approaches demand user interaction, which are inappropriate for large-scale image collection. To improve the accuracy of web image retrieval in a practicable manner, we propose a novel re-ranking algorithm to explore the cluster information of the image set. First, we build spectral graph on images that retrieved bysearch engine, and remove isolated nodes as noisy images. then, we select positive samples from the most dominant cluster in initial top-ranked images, and the samples are used for semi-supervised learning and ranking. Our algorithm is online and non-feedback. Experiments on two public databases demonstrate that our algorithm outperforms the state-of-the-art approaches. © 2012 ACM.

关键词： Supervised learning

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Dana36: A Multi-Camera Image Dataset for Object Identification in Surveillance Scenarios

Dana36: A Multi-Camera Image Dataset for Object Identificati...

引用

9th IEEE International conference on Advanced Video and Signal-Based Surveillance (AVSS)

作者： Pers, Janez Kenk, Vildana Sulic Mandeljc, Rok Kristan, Matej Kovacic, Stanislav Univ Ljubljana Fac Elect Engn SI-100 Ljubljana Slovenia

ISBN: (纸本)9780769547978

We present a novel dataset for evaluation of object matching and recognition methods in surveillance scenarios. Dataset consists of more than 23,000 images, depicting 15 persons and nine vehicles. A ground truth data - the identity of each person or vehicle - is provided, along with the coordinates of the bounding box in the full camera image. the dataset was acquired from 36 stationary camera views using a variety of surveillance cameras with resolutions ranging from standard VGA to three megapixel. 27 cameras observed the persons and vehicles in an outdoor environment, while the remaining nine observed the same persons indoors. the activity of persons was planned in advance;they drive the cars to the parking lot, exit the cars and walk around the building, through the main entrance, and up the stairs, towards the first floor of the building. the intended use of the dataset is performance evaluation of computer vision methods that aim to (re) identify people and objects from many different viewpoints in different environments and under variable conditions. Due to variety of camera locations, vantage points and resolutions, the dataset provides means to adjust the difficulty of the identification task in a controlled and documented manner. An interface for easy use of dataset within Matlab is provided as well, and the data is complemented by baseline results using a basic color histogram-based descriptor. While the cropped images of persons and vehicles represent the primary data in our dataset, we also provide full-frame images and a set of tracklets for each object as a courtesy to the dataset users.

关键词： Vehicles

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Human Daily Action Analysis with Multi-view and Color-Depth Data 12

Human Daily Action Analysis with Multi-view and Color-Depth ...

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12th European conference on computer vision (ECCV)

作者： Cheng, Zhongwei Qin, Lei Ye, Yituo Huang, Qingming Tian, Qi Chinese Acad Sci Grad Univ Beijing 100190 Peoples R China ICT CAS Key Lab Intelli Info Proc Beijing 100190 Peoples R China Univ Texas San Antonio San Antonio TX 78249 USA

ISBN: (纸本)9783642338687;9783642338670

Improving human action recognition in videos is restricted by the inherent limitations of the visual data. In this paper, we take the depth information into consideration and construct a novel dataset of human daily actions. the proposed ACT4(2) dataset provides synchronized data from 4 views and 2 sources, aiming to facilitate the research of action analysis across multiple views and multiple sources. We also propose a new descriptor of depth information for action representation, which depicts the structural relations of spatiotemporal points within action volume using the distance information in depth data. In experimental validation, our descriptor obtains superior performance to the state-of-the-art action descriptors designed for color information, and more robust to viewpoint variations. the fusion of features from different sources is also discussed, and a simple but efficient method is presented to provide a baseline performance on the proposed dataset.

关键词： Daily action Multi-View RGB-D Depth descriptor

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the narrow-band assumption in log-chromaticity space

The narrow-band assumption in log-chromaticity space

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11th European conference on computer vision, ECCV 2010

作者： Eibenberger, Eva Angelopoulou, Elli Pattern Recognition Lab. University of Erlangen-Nuremberg Germany International Max Planck Research School for Optics and Imaging Germany Erlangen Germany

ISBN: (纸本)9783642357398

Despite the strengths and popularity of the log-cromaticity space (LCS), there is still a significant amount of concern regarding its narrow-band assumption (NBA). though not always necessary, this assumption is relatively common, as it leads to elegant formulations. We present a scheme for evaluating whether a deviation from the NBA will have an impact on the expected LCS values. We also introduce two metrics for measuring the divergence from the expected behavior under the NBA in LCS. Lastly, we empirically analyze how different types of reflectance spectra are affected in varying degrees by this assumption. For example, experiments with real and synthetic data show that the violation of the NBA typically has insignificant impact on bright unsaturated colors. © 2012 Springer-Verlag.

关键词： computers

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Real-time performance of textile electrodes in electromyogram pattern-recognition based prosthesis control

Real-time performance of textile electrodes in electromyogra...

引用

IEEE-EMBS International conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering

作者： Tao, Dandan Zhang, Haoshi Wu, Zhenxing Li, Guanglin Harbin Institute of Technology Graduate School Shenzhen Guangdong 518055 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong 518055 China

ISBN: (纸本)9781457721779

Textile electrode is flexible, folding, washable and biocompatible with skin. With these advantages, the textile electrodes should be an ideal alternative for electromyogram (EMG) recordings in clinical applications. In this study, a textile electrode system was used for EMG signal recordings and its usability and performance in classifying different arm and hand movements were evaluated through real-time pattern recognition control of virtual myoelectric arm. Our results showed that the offline average classification accuracy over seven able-bodied subjects for all ten movements was 91.81%, compared to 96.54% for six basic movements. the real-time performance in operating a virtual arm was quantified with three measures: selection time, completion time, and completion time. Averagely, the seven subjects achieved a motion selection time of approximately 0.36 s, and a completion time of less than 2 s, and a completion rate of around 82%. these pilot results suggest that the textile electrodes could work well in real-time control of multifunctional myoelectric prosthesis. © 2012 IEEE.

关键词： Real time control

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Support vector machine with mixture of kernels for image classification 1

引用

7th IFIP International conference on Intelligent Information Processing, IIP 2012

作者： Tian, Dongping Zhao, Xiaofei Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (数字)9783642328916

ISBN: (纸本)9783642328909

Image classification is a challenging problem in computer vision. Its performance heavily depends on image features extracted and classifiers to be constructed. In this paper, we present a new support vector machine with mixture of kernels (SVM-MK) for image classification. On the one hand, the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as possible. SVM-MK, on the other hand, is constructed to shoot for better classification performance. Experimental results on the Berg dataset show that the proposed image feature representation method together with the constructed image classifier, SVMMK, can achieve higher classification accuracy than conventional SVM with any single kernels as well as compare favorably with several state-of-the-art approaches. © 2012 IFIP International Federation for Information Processing.

关键词： Image classification

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Double least squares pursuit for sparse decomposition 1

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7th IFIP International conference on Intelligent Information Processing, IIP 2012

作者： Li, Wanyi Wang, Peng Qiao, Hong Institute of Automation Chinese Academy of Sciences No. 95 of Zhongguancun East Road Haidian District Beijing 100190 China

ISBN: (数字)9783642328916

ISBN: (纸本)9783642328909

Sparse decomposition has been widely used in numerous applications, such as image processing, pattern recognition, remote sensing and computational biology. Despite plenty of theoretical developments have been proposed, developing, implementing and analyzing novel fast sparse approximation algorithm is still an open problem. In this paper, a new pursuit algorithm Double Least Squares Pursuit (DLSP) is proposed for sparse decomposition. In this algorithm, the support of the solution is obtained by sorting the coefficients which are calculated by the first Least-Squares, and then the non-zero values over this support are detected by the second Least-Squares. the results of numerical experiment demonstrate the effectiveness of the proposed method, which is with less time complexity, more simple form, and gives close or even better performance compared to the classical Orthogonal Matching Pursuit (OMP) method. © 2012 IFIP International Federation for Information Processing.

关键词： Approximation algorithms

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