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检索条件"任意字段=MIPPR 2011: Pattern Recognition and Computer Vision"

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Automatic object segmentation from large scale 3D urban point clouds through manifold embedded mode seeking 11

Automatic object segmentation from large scale 3D urban poin...

引用

19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Yu, Zhiding Xu, Chunjing Liu, Jianzhuang Au, Oscar C. Tang, Xiaoou Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Information Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781450306164

This paper presents a system that can automatically segment objects in large scale 3D point clouds obtained from urban ranging images. The system consists of three steps: The first one involves a ground detection process that can detect relatively complex terrain and separate it from other objects. The second step superpixelizes the remaining objects to speed up the segmentation process. In the final step, a manifold embedded mode seeking method is adopted to segment the point clouds. Even though the segmentation of urban objects is a challenging problem in terms of accuracy and problem scale, our system can efficiently generate very good segmentation results. The proposed manifold learning effectively improves the segmentation performance due to the fact that continuous artificial objects often have manifold-like structures. Copyright 2011 ACM.

关键词： Image segmentation

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Research for predicting road skid resistance based on machine vision

Research for predicting road skid resistance based on machin...

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GeoHunan International Conference

作者： Peng, Kai Zhou, Xing-Lin College of Mechanical Engineering Hebei University of Technology Tianjin 300130 China School of Automobile and Traffic Engineering Wuhan University of Science and Technology Hubei Wuhan 430081 China

ISBN: (纸本)9780784476246

The texture of the pavement surface and its ability to resist the polishing effect of traffic is of prime importance in providing skidding resistance. Skid resistance is a measure of the resistance of pavement surface to sliding or skidding of the vehicle. Road surface texture is essential for pavement skid-resistance. However, its measurement is only possible in the laboratory on cores taken from trafficked roads, and is time consuming. Now it is necessary to develop new methods of monitoring road on-site efficiently. In this dissertation, a system has been developed for measuring the road texture, form and angularity of aggregate based on image analysis, which consists of a line-laser, CCD and a computer. The line-laser can scan a field of 100mm for each time. The form and angularity of aggregate and microtexture of pavement surface is measured by analyzing image of laser. And the character of road microtexture can be recognized by pattern recognition. Thus the methods which were used to measure the shape characteristics of aggregates are unified. Basing on the principles set for the sand patch method, the mathematic model and hardware designing were given. A comparative study was performed to find the British Pendulum Skid Resistance Number for a number of mixes. The experimental results show that the vision measurement system can efficiently improve the testing speed and the accuracy on-site. © 2011 ASCE.

关键词： Skid resistance

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Engineering Applications of Neural Networks 2011

引用

丛书名： IFIP Advances in Information and Communication Technology

2011年

作者： Lazaros S. Iliadis Chrisina Jayne

ISBN: (数字)9783642239571

ISBN: (纸本)9783642239564

The two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th International Conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 International Conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. The 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. The first volume includes the papers that were accepted for presentation at the EANN 2011 conference. They are organized in topical sections on computer vision and robotics, self organizing maps, classification/pattern recognition, financial and management applications of AI, fuzzy systems, support vector machines, learning and novel algorithms, reinforcement and radial basis function ANN, machine learning, evolutionary genetic algorithms optimization, Web applications of ANN, spiking ANN, feature extraction minimization, medical applications of AI, environmental and earth applications of AI, multi layer ANN, and bioinformatics. The volume also contains the accepted papers from the Workshop on Applications of Soft Computing to Telecommunication (ASCOTE 2011), the Workshop on Computational Intelligence Applications in Bioinformatics (CIAB 2011), and the Second Workshop on Informatics and Intelligent Systems Applications for Quality of Life Information Services (ISQLIS 2011).

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Image matching algorithms in stereo vision using address-event- representation: A theoretical study and evaluation of the different algorithms

Image matching algorithms in stereo vision using address-eve...

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作者： Dominguez-Morales, M. Cerezuela-Escudero, E. Jimenez-Fernandez, A. Paz-Vicente, R. Font-Calvo, J.L. Iñigo-Blasco, P. Linares-Barranco, A. Jimenez-Moreno, G. Department of Architecture and Computer Technology University of Seville Seville Spain

ISBN: (纸本)9789898425720

Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from cameras that capture reality for a short period of time. They are renewed and transmitted at a rate of 25-30 fps (typical real-time scenario). Digital video processing has to process each frame in order to obtain a filter result or detect a feature on the input. In stereo vision, existing algorithms use frames from two digital cameras and process them pixel by pixel until it is found a pattern match in a section of both stereo frames. Spike-based processing is a relatively new approach that implements the processing by manipulating spikes one by one at the time they are transmitted, like a human brain. The mammal nervous system is able to solve much more complex problems, such as visual recognition by manipulating neuron's spikes. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event- Representation (AER) is achieving nowadays very high performances. In this work we study the existing digital stereo matching algorithms and how do they work. After that, we propose an AER stereo matching algorithm using some of the principles shown in digital stereo methods.

关键词： Stereo vision

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Max-margin Clustering: Detecting Margins from Projections of Points on Lines

Max-margin Clustering: Detecting Margins from Projections of...

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IEEE Conference on computer vision and pattern recognition

作者： Raghuraman Gopalan Jagan Sankaranarayanan Center for Automation Research University of Maryland NEC Labs

ISBN: (纸本)9781457703942

Given a unlabelled set of points X ∈ R~N belonging to k groups, we propose a method to identify cluster assignments that provides maximum separating margin among the clusters. We address this problem by exploiting sparsity in data points inherent to margin regions, which a max-margin classifier would produce under a supervised setting to separate points belonging to different groups. By analyzing the projections of X on the set of all possible lines L in R~N, we first establish some basic results that are satisfied only by those line intervals lying outside a cluster, under assumptions of linear separability of clusters and absence of outliers. We then encode these results into a pair-wise similarity measure to determine cluster assignments, where we accommodate non-linearly separable clusters using the kernel trick. We validate our method on several UCI datasets and on some computer vision problems, and empirically show its robustness to outliers, and in cases where the exact number of clusters is not available. The proposed approach offers an improvement in clustering accuracy of about 6% on the average, and up to 15% when compared with several existing methods.

关键词： outliers PROJECTION Clusters images computer vision lines lines Tumor margin status

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Dirichlet Process Mixture Models on Symmetric Positive Definite Matrices for Appearance Clustering in Video Surveillance Applications

Dirichlet Process Mixture Models on Symmetric Positive Defin...

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IEEE Conference on computer vision and pattern recognition

作者： Anoop Cherian Vassilios Morellas Nikolaos Papanikolopoulos Saad J. Bedros Department of Computer Science & Engineering University of Minnesota Honeywell

ISBN: (纸本)9781457703942

Covariance matrices of multivariate data capture feature correlations compactly, and being very robust to noise, they have been used extensively as feature descriptors in many areas in computer vision, like, people appearance tracking, DTI imaging, face recognition, etc. Since these matrices do not adhere to the Euclidean geometry, clustering algorithms using the traditional distance measures cannot be directly extended to them. Prior work in this area has been restricted to using K-means type clustering over the Riemannian space using the Riemannian metric. As the applications scale, it is not practical to assume the number of components in a clustering model, failing any soft-clustering algorithm. In this paper, a novel application of the Dirichlet Process Mixture Model framework is proposed towards unsupervised clustering of symmetric positive definite matrices. We approach the problem by extending the existing K-means type clustering algorithms based on the logdet divergence measure and derive the counterpart of it in a Bayesian framework, which leads to the Wishart-Inverse Wishart conjugate pair. Alternative possibilities based on the matrix Frobenius norm and log-Euclidean measures are also proposed. The models are extensively compared using two real-world datasets against the state-of-the-art algorithms and demonstrate superior performance.

关键词： Positive definite matrix Cluster model video monitoring Riemann space distance measurement Clustering algorithms Cluster Analysis CENTROSYMMETRIC images computer vision matrices

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Edge-preserving single image super-resolution 11

Edge-preserving single image super-resolution

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19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Zhou, Qiang Chen, Shifeng Liu, Jianzhuang Tang, Xiaoou Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781450306164

This paper proposes a novel approach to single image super-resolution. First, an image up-sampling scheme is proposed which takes the advantages of both bilateral filtering and mean shift image segmentation. Then we use a shock filter to enhance strong edges in the initial up-sampling result and obtain an intermediate high-resolution image. Finally, we enforce a reconstruction constraint on the high-resolution image so that fine details can be inferred by back projection. Since strong edges in the intermediate result are enhanced, ringing artifacts can be suppressed in the back projection step. We compare our algorithm with several state-of-the-art image super-resolution algorithms. Qualitative and quantitative experimental results demonstrate that our approach performs the best. Copyright 2011 ACM.

关键词： Image segmentation

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AFiT - Atrial fibrillation ablation planning tool

AFiT - Atrial fibrillation ablation planning tool

引用

16th International Workshop on vision, Modeling and Visualization, VMV 2011

作者： Brost, A. Bourier, F. Kleinoeder, A. Raab, J. Koch, M. Stamminger, M. Hornegger, J. Strobel, N. Kurzidim, K. Pattern Recognition Lab. Friedrich-Alexander-University Erlangen-Nuremberg Erlangen Germany Klinik fur Herzrhythmusstorungen Krankenhaus Barmherzige Brüder Regensburg Germany Computer Graphics Group Friedrich-Alexander-University Erlangen-Nuremberg Erlangen Germany Siemens AG Forcheim Germany

ISBN: (纸本)9783905673852

The planning of cryo-balloon ablations for treatment of atrial fibrillation is a crucial task for a physician as he has to determine which size of the balloon catheter is required for isolation at each pulmonary vein. Today, the diameter of the pulmonary vein's ostium is measured in a pre-operative data set to determine which type of catheter is most appropriate. We present a novel tool that visualizes a cryo-balloon catheter model within a 3-D model representing a segmented left atrium. Using this approach, physicians are able to better assess the catheter fit. So far, measurement of the pulmonary vein diameters have been performed by evaluation of 2-D slices taken from pre-operative data sets. The first feedback obtained by physicians was very encouraging as this tool offers better insights for balloon catheter ablation procedures. © The Eurographics Association 2011.

关键词： Catheters

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Global Stereo Matching Leveraged by Sparse Ground Control Points

Global Stereo Matching Leveraged by Sparse Ground Control Po...

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IEEE Conference on computer vision and pattern recognition

作者： Liang Wang Ruigang Yang Center for Visualization and Virtual Environments University of Kentucky

ISBN: (纸本)9781457703942

We present a novel global stereo model that makes use of constraints from points with known depths, i.e., the Ground Control Points (GCPs) as referred to in stereo literature. Our formulation explicitly models the influences of GCPs in a Markov Random Field. A novel GCPs-based regularization term is naturally integrated into our global optimization framework in a principled way using the Bayes rule. The optimal solution of the inference problem can be approximated via existing energy minimization techniques such as graph cuts used in this paper. Our generic probabilistic framework allows GCPs to be obtained from various modalities and provides a natural way to integrate the information from multiple sensors. Quantitative evaluations demonstrate the effectiveness of the proposed formulation for regularizing the ill-posed stereo matching problem and improving reconstruction accuracy.

关键词： Image color analysis Stereo vision Three dimensional displays Image segmentation Equations Sensors Accuracy

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Salient Coding for Image Classification

Salient Coding for Image Classification

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IEEE Conference on computer vision and pattern recognition

作者： Yongzhen Huang Kaiqi Huang Yinan Yu Tieniu Tan National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781457703942

The codebook based (bag-of-words) model is a widely applied model for image classification. We analyze recent coding strategies in this model, and find that saliency is the fundamental characteristic of coding. The saliency in coding means that if a visual code is much closer to a descriptor than other codes, it will obtain a very strong response. The salient representation under maximum pooling operation leads to the state-of-the-art performance on many databases and competitions. However, most current coding schemes do not recognize the role of salient representation, so that they may lead to large deviations in representing local descriptors. In this paper, we propose "salient coding", which employs the ratio between descriptors' nearest code and other codes to describe descriptors. This approach can guarantee salient representation without deviations. We study salient coding on two sets of image classification databases (15-Scenes and PASCAL VOC2007). The experimental results demonstrate that our approach outperforms all other coding methods in image classification.

关键词： Image classification Descriptors Codes Subject Headings coding

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