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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

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Advances in Discrete Tomography and Its Applications 1

引用

丛书名： Applied and Numerical Harmonic Analysis

2007年

作者： Gabor T. Herman Attila Kuba

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A Geometry-Based Local Descriptor for Range Data

A Geometry-Based Local Descriptor for Range Data

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Fredrik Viksten Klas Nordberg Image Coding Group Department of Electrical Engineering Linköping university Sweden Computer Vision Laboratory Department of Electrical Engineering Linköping university Sweden

ISBN: (纸本)9781424431618;9780769530673

We present a novel local descriptor for range data that can describe one or more planes or lines in a local region. It is possible to recover the geometry of the described local region and extract the size, position and orientation of each local plane or line-like structure from the descriptor. This gives the descriptor a property that other popular local descriptors for range data, such as spin images or point signatures, does not have. The estimation of the descriptor is dependant on estimation of surface normals but does not depend on the specific normal estimation method used. It is shown that is possible to extract how many planar surface regions the descriptor represents and that this could be used as a point-of-interest detector.

关键词： Tensile stress Layout computer vision Geometry Data mining Digital images computer applications Application software Image coding Laboratories

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Neural Information Processing 1

引用

丛书名： Lecture Notes in computer Science

1000年

ISBN: (数字)9783540691587

ISBN: (纸本)9783540691549

These two-volume books comprise the post-conference proceedings of the 14th International Conference on Neural Information Processing (ICONIP 2007) held in Kitakyushu, Japan, during November 13–16, 2007. The Asia Paci?c Neural Network Assembly (APNNA) was founded in 1993. The ?rst ICONIP was held in 1994 in Seoul, Korea, sponsored by APNNA in collaboration with regional organizations. Since then, ICONIP has consistently provided prestigious opp- tunities for presenting and exchanging ideas on neural networks and related ?elds. Research ?elds covered by ICONIP have now expanded to include such ?elds as bioinformatics, brain machine interfaces, robotics, and computational intelligence. We had 288 ordinary paper submissions and 3 special organized session p- posals. Although the quality of submitted papers on the average was excepti- ally high, only 60% of them were accepted after rigorous reviews, each paper being reviewed by three reviewers. Concerning special organized session prop- als, two out of three were accepted. In addition to ordinary submitted papers, we invited 15 special organized sessions organized by leading researchers in emerging ?elds to promote future expansion of neural information processing. ICONIP 2007 was held at the newly established Kitakyushu Science and Research Park in Kitakyushu, Japan. Its theme was “Towards an Integrated Approach to the Brain—Brain-Inspired Engineering and Brain Science,” which emphasizes the need for cross-disciplinary approaches for understanding brain functions and utilizing the knowledge for contributions to the society. It was jointly sponsored by APNNA, Japanese Neural Network Society (JNNS), and the 21st century COE program at Kyushu Institute of Technology.

关键词： Artificial Intelligence Computation by Abstract Devices pattern recognition Information Systems Applications (incl. Internet) Database Management Image Processing and computer vision

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A simple tracking approach for line extraction

A simple tracking approach for line extraction

引用

International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Liang Chen Lei Guo Ya-Ping Wang Shi-Wei Gao Yong Yu College of Automation Northwest Polytechnical University Xi'an Shaanxi China

Line extraction plays an important role in many applications as mid-level feature description; the problem is how to get accurate location of line effectively. In this paper, the extraction is simplified by edge tracking with adding some constraints which ensure the edge be linked near to the line. It is a strategy that made a feasible way to obtain lines. Following edge detecting, the proposed approach obtains lines by tracking edge with priority direction, inertia tracking, judging and rectifying linear relation real-time. After such constraints on the tracking process, the edge is linked to a line. Experiments show varied results of proposed approach and the contrast to Hough transform, and it can be seen that the line extracted is more effective than latter.

关键词： Image edge detection Joining processes computer vision pattern analysis pattern recognition Eigenvalues and eigenfunctions Pixel Wavelet analysis Educational institutions

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Annotated Databases for the recognition of Screen-Rendered Text

Annotated Databases for the Recognition of Screen-Rendered T...

引用

International Conference on Document Analysis and recognition

作者： S. Wachenfeld H.-U. Klein X. Jiang Computer Vision and Pattern Recognition Group Department of Computer Science University of Münster Germany

The recognition of screen-rendered text is a novel task. It is performed e.g. by translation tools which allow users to click on any text on the screen and give a translation. Also some commercial OCR programs start to address the problem of reading screenshots. Optical character recognition on screen-shot images can be very challenging due to very small and smoothed fonts. In order to build and compare recognition approaches for screen-rendered text, the availability of standard databases is a fundamental prerequisite. In this paper two freely available databases are presented, one that consists of annotated screenshot images of 28080 single characters and another holding 400 words extracted from documents plus 2 400 generated isolated words. Both databases include meta-information such as x-height, font type, style and rendering conditions. At the example of a developed recognition system, it is shown how these databases can serve for training, testing and optimization.

关键词： Text recognition Image databases Optical character recognition software System testing pattern recognition Rendering (computer graphics) Operating systems Character recognition Character generation Application software

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vision based gesture recognition for human-robot symbiosis

Vision based gesture recognition for human-robot symbiosis

引用

International Conference on computer and Information Technology (ICCIT)

作者： Md. Al-Amin Bhuiyan Md. Ezharul Islam Nasima Begum Md. Hasanuzzaman Chang Hong Liu Haruki Ueno Jahangirnagar University Dhaka Bangladesh University of Dhaka Dhaka Bangladesh University of Hull Hull UK National Institute of Information and Communications Technology Tokyo Japan National Institute of Informatics Tokyo Japan

This paper presents a vision based gesture recognition system for human-robot symbiosis. The system is based on the visual information of the face and is commenced with the recognition of face gesture by connected component analysis of the skin color segmentation of images in HSV color model and neural network based pattern-matching strategies. On gesture recognition, robot is being instructed to perform certain tasks by issuing commands. The system is capable of recognizing static gestures comprised of the face poses, and dynamic gestures of face in motion. The effectiveness of the system has been justified over some experiments. The system has been demonstrated with an entertainment robot named ldquoAIBOrdquo as a human-robot symbiotic relationship.

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Facial Template Synthesis based on SIFT Features

Facial Template Synthesis based on SIFT Features

引用

IEEE Workshop on Automatic Identification Advanced Technologies

作者： Ajita Rattani D. R. Kisku Andrea Lagorio Massimo Tistarelli Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India Computer Vision Laboratory University of Sassari Alghero Italy

This paper proposes a procedure for facial template synthesis based on features extracted from multiple facial instances with varying pose. The proposed system extracts the rotation, scale and translation invariant SIFT features, also having high discrimination ability, from the frontal and half left and right profiles of an individual face images. These affine invariant features obviate the need of ad-hoc algorithms to register features of side profiles against frontal profiles for feature-set augmentation. An augmented feature set is then formed from the fusion of features from frontal and side profiles of an individual, after removing feature redundancy. The augmented feature sets of database and query images are matched using the Euclidean distance and Point pattern matching techniques. The experimental results are compared with the system using only frontal face images for both the matching strategies. The reported results prove the efficacy of the proposed system.

关键词： Face recognition Feature extraction Iterative algorithms pattern matching Biometrics Fingerprint recognition computer science computer vision Laboratories Redundancy

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Data decomposition and spatial mixture modeling for part based model

Data decomposition and spatial mixture modeling for part bas...

引用

11th Asian Conference on computer vision, ACCV 2012

作者： Zhang, Junge Huang, Yongzhen Huang, Kaiqi Wu, Zifeng Tan, Tieniu National Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9783642373305

This paper presents a system of data decomposition and spatial mixture modeling for part based models. Recently, many enhanced part based models (with e.g., multiple features, more components or parts) have been proposed. Nevertheless, those enhanced models bring high computation cost together with the risk of over-fitting. To tackle this problem, we propose a data decomposition method for part based models which not only accelerates training and testing process but also improves the performance on average. Besides, the original part based model uses a strict rigid structural model to describe the distribution of each part location. It is not "deformable" enough, especially for those instances with different viewpoints or poses in the same aspect ratio. To address this problem, we present a novel spatial mixture modeling method. The spatial mixture embedded model is then integrated into the proposed data decomposition framework. We evaluate our system on the challenging PASCAL VOC2007 and PASCAL VOC2010 datasets, demonstrating the state-of-the-art performance compared with other related methods in terms of accuracy and efficiency. © 2013 Springer-Verlag.

关键词： Aspect ratio

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The Relationship Between Kernel and Classifier Fusion in Kernel-Based Multi-Modal pattern recognition: An Experimental Study

The Relationship Between Kernel and Classifier Fusion in Ker...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： David Windridge Vadim Mottl Alexander Tatarchuk Andrey Eliseyev Centre for Vision Speech and Signal Processing University of Surrey Guildford UK Computing Center Russian Academy of Science Moscow Russia Moscow Institute of Physics and Technology Moscow Russia

Two distinct principles of multi-modal kernel-based pattern recognition, kernel and classifier fusion, are demonstrated to share common underlying characteristics via the use of a novel kernel-based technique for combining modalities under fully general conditions, namely, the neutral-point method. This method presents a conservative kernel-based strategy for dealing with missing and disjoint training data in independent measurement modalities that can be theoretically shown to default to the sum rule classification scheme. Results of comparative experiments indicate that the neutral-point technique loses relatively little classification information with respect to coincident training data, and is in fact preferable for independent kernels produced by different physical modalities due to its better error-cancellation properties.

关键词： Kernel pattern recognition Training data Sensor fusion Machine learning Cybernetics Speech processing Biomedical signal processing computer vision Physics computing

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Perceptual Surface Roughness Classification of 3D Textures Using Support Vector Machines

Perceptual Surface Roughness Classification of 3D Textures U...

引用

IEEE International Workshop on Haptic, Audio and Visual Environments and Their Applications

作者： Troy L. McDaniel Sethuraman Panchanathan Center for Cognitive Ubiquitous Computing Department of Computer Science and Engineering Arizona State University Tempe AZ USA

Perceptual surface roughness classification describes how a surface's texture feels haptically in terms of perceptual categories such as smooth, rough, bumpy, etc. computer vision and pattern recognition algorithms which estimate a surface's perceptual roughness have a wide range of application areas including robotics, assistive devices, telesurgery and teleperception. In this paper, we propose a novel approach to perceptual surface roughness classification that, unlike previous approaches, is designed to handle multiple roughness categories within the same image. The steps of our approach include (1) texton extraction and classification using a multi-class, non-linear Support Vector Machine; (2) segmentation using the Iterated Conditional Modes algorithm; and (3) overall perceptual roughness classification using a Nearest Neighbor classifier. The proposed approach is evaluated using visio-haptic subjective measures of roughness on images of the 3D texture of real world objects.

关键词： Rough surfaces Surface roughness Surface texture Support vector machines Support vector machine classification computer vision pattern recognition Application software Robot vision systems Image segmentation

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