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

共 1015 条记录，以下是211-220 订阅

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Modeling Images as Mixtures of Reference Images

Modeling Images as Mixtures of Reference Images

引用

IEEE-computer-Society Conference on computer vision and pattern recognition Workshops

作者： Perronnin, Florent Liu, Yan Textual and Visual Pattern Analysis (TVPA) Xerox Research Centre Europe (XRCE) France

ISBN: (纸本)9781424439928

A state-of-the-art approach to measure the similarity of two images is to model each image by a continuous distribution, generally a Gaussian mixture model (GMM), and to compute a probabilistic similarity between the GMMs. One limitation of traditional measures such as the Kullback-Leibler (KL) divergence and the Probability Product Kernel (PPK) is that they measure a global match of distributions. This paper introduces a novel image representation. We propose to approximate an image, modeled by a GMM, as a convex combination of K reference image GMMs, and then to describe the image as the K-dimensional vector of mixture weights. The computed weights encode a similarity that favors local matches (i.e. matches of individual Gaussians) and is therefore fundamentally different from the KL or PPK. Although the computation of the mixture weights is a convex optimization problem, its direct optimization is difficult. We propose two approximate optimization algorithms: the first one based on traditional sampling methods, the second one based on a variational bound approximation of the true objective function. We apply this novel representation to the image categorization problem and compare its performance to traditional kernel-based methods. We demonstrate on the PASCAL VOC 2007 dataset a consistent increase in classification accuracy

关键词： Image representation

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An automatic remote sensing mosaic algorithm based on modified SIFT feature

An automatic remote sensing mosaic algorithm based on modifi...

引用

mippr 2009 - Remote Sensing and GIS Data Processing and Other Applications: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Chen, Zhong Deng, He Wang, Guoyou Intelligence Control Insititute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Multi-Spectral Information Processing State Key Laboratory Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

Image mosaic technology is an important research field of image processing and a research focus on the computer vision and computer graphics. The traditional method is to select the feature points by manual selection method, which faces the problem of low reliability and efficiency in the batch of the image mosaic. The SIFT features have many properties that make them suitable for matching differing images of an object or scene. But the computation amount and the computation complexity are so great, which restricts the further real time application. So an automatic remote sensing image mosaic algorithm based on modified SIFT feature is presented in this paper to solve these problems. The method presented in this paper consisted of three steps: noise removal, modified SIFT feature registration and automatic mosaic. The test results show the modified mosaic algorithm based on the SIFT feature can improve the matching accuracy and reduce the computation times. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： computer graphics

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Fast background image update in multi-touch system

Fast background image update in multi-touch system

引用

mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Yang, Tao Li, Xiang Wang, Yongtian Liu, Yue School of Optics and Electronics Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9780819478061

Background subtraction technique has been widely used in the single camera based multi-touch system. The solution based on fixed-rate background accumulation can only be used to the applications with gradual change of ambient lightings. This paper presents a solution to update background by detecting ambient lightings, which enables the multi-touch system to be operated under the conditions of rapid or complicated change of ambient lightings. Experimental results show that with the help of the presented solutions, the ghost points are efficiently reduced and the system can adapt to the changes of ambient lighting in 1 second. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： computer vision

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Ensemble Manifold Regularization

Ensemble Manifold Regularization

引用

IEEE-computer-Society Conference on computer vision and pattern recognition Workshops

作者： Geng, Bo Xu, Chao Tao, Dacheng Yang, Linjun Hua, Xian-Sheng Peking Univ Key Lab Machine Percept Beijing 100871 Peoples R China Univ Technol Sydney Fac Engn & Informat Technol Ctr Quantum Computat & Intelligen Syst Sydney NSW 2007 Australia Microsoft Res Asia Beijing 100190 Peoples R China Microsoft Corp Redmond WA 98052 USA

ISBN: (纸本)9781424439928

We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning problems. Unfortunately it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, pure cross-validation is considered but it does not necessarily scale up. A second problem derives from the suboptimality incurred by discrete grid search and overfitting problems. As a consequence, we developed an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR very carefully so that it (a) learns both the composite manifold and the semi-supervised classifier jointly;(b) is fully automatic for learning the intrinsic manifold hyperparameters implicitly;(c) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption;and (d) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Extensive experiments over both synthetic and real datasets show the effectiveness of the proposed framework.

关键词： Supervised learning

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mippr 2009 - Automatic Target recognition and Image Analysis

MIPPR 2009 - Automatic Target Recognition and Image Analysis

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mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

ISBN: (纸本)9780819478061

The proceedings contain 186 papers. The topics discussed include: removing shift-variant motion blur from an image using Poisson interpolation;online real AdaBoost with co-training for object tracking;object detection based on multiscale discrete points sampling and grouping;real-time detection of removed objects based on multi-cue fusion;tabletop interaction system using plate position recognition by computer vision;transfer network learning based remote sensing target recognition;optimum selection of common master image for multitemporal InSAR;real-time object detection based on the improved boosted features;an automated detection method of permanent scatterers in radar interferometry based on ICA;the small infrared target detection in complicated background based on adaptive morphological filter;a fuzzy-logic-based context model for multiscale segmentation fusion;and recognition of sand dredges in the Changjiang River based on ASAR remote sensing data.

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Fruit shape detection by optimizing Chan-Vese model

Fruit shape detection by optimizing Chan-Vese model

引用

mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Shou, Zhouxiang Wang, Qihui Gui, Jiangsheng Wang, Yuhuai Hangzhou Normal University Hangzhou 310012 China Dept. of Information and Electronic Zhejiang Sci.-Tech. University Hangzhou 310018 China

ISBN: (纸本)9780819478061

Applications of machine vision for automated inspection and sorting of fruits have been widely studied by scientists and engineers. In these applications, edge detection, segmentation, and shape recovery are difficult problem. Previous studies have usually adopted some preprocessing such as noise removal and motion deblurring before using a threshold method to detect shape boundary. In many cases, however, this manner is troubled and not unified and does not work well. This research proposes a novel approach for fruit shape detection in RGB spaces based on a fast level set method and the Chan-Vese model. We called it optimizing Chan-Vese model (OCV). This new algorithm is fast because it needs no re-initialization procedure and thus is suitable for fruit sorting. OCV has three advantages compared to traditional methods. First, it provides a unified framework for detection fruit shape boundary, requiring no preprocessing and even if the raw image is noisy or blurred. Second, it can detect boundaries for images of fruit with multi-colored edges, which traditional methods fail to deal with. Third, it is processed directly in colour space without any transformations that can lose much information. The proposed method has been applied to fruit shape detection with promising results. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： computer vision

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Intelligent Pedestrian Detection System in Semi-dark Environment

Intelligent Pedestrian Detection System in Semi-dark Environ...

引用

International Conference of Soft Computing and pattern recognition

作者： Gan, Yi Al-Jumaily, Adel Univ Technol Sydney Fac Engn Sch Elect Mech & Mechatron Syst Sydney NSW 2007 Australia

ISBN: (纸本)9781424453306

computer vision techniques have been widely used in various applications. In recent years, as energy efficiency have gradually become a important issues, computer vision techniques can be integrated into a smart control system that helps increase the energy efficiency by controlling the turn on of the light based on human detection. However, implement such system that detect walking human in a semi-dark environment remains a challenge. This paper proposes a novel detection technique combining movement analysis and SVM classifier to tackle this problem. This technique consist of a few steps: a statistical background model to segment moving objects as foreground, followed by an analysis model to generate pedestrian candidates based on the movement of foreground objects and lastly a SVM classifier that verify the pedestrian candidates based on the shape features.

关键词： Human Dectection Semi dark enviroment vision SVM

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HUMAN GAIT recognition USING DIFFERENCE BETWEEN FRAMES

HUMAN GAIT RECOGNITION USING DIFFERENCE BETWEEN FRAMES

引用

4th International Conference on computer vision Theory and Applications

作者： Karami, Mazaher Ahmadyfard, Alireza Shahrood Univ Technol Dept Elect Sch Robot & Elect Engn Shahrood Iran

ISBN: (纸本)9789898111692

In this paper, we address the problem of human identification using gait. Considering the recent work of Lee et al. (Lee et al., 2007) proposed for gait recognition. First we will introduce the algorithm proposed by Lee et al.. This method has two main steps: (1) extract key frames to define the gait cycle pattern, and (2) compute Shape Variation-based frieze patterns. These patterns are then used to classify and perform the gait identification. We modify the utilized features in this approach. We try to omit redundant features based on the effect of each feature on recognition rate and in next step, we improve performance of this approach by making some changes in way of feature extraction. Finally, we use the statistical characteristics of employed features instead of direct applying of remaining features. We test the proposed method on CASIA database. The experimental results are used to compare the proposed method with Lee et al. method.

关键词： Biometric Frieze pattern Gait recognition

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Real-Time Stereo Matching Using Memory-Efficient Belief Propagation for High-Definition 3D Tele-Presence Systems

Real-Time Stereo Matching Using Memory-Efficient Belief Prop...

引用

14th Iberoamerican Congress on pattern recognition

作者： Perez, Jesus M. Sanchez, Pablo Martinez, Marcos Univ Cantabria Av Los Castros S-N E-39005 Santander Spain DS2 E-46980 Valencia Spain

ISBN: (纸本)9783642102677

High-definition 3D video is one of the features that the next generation of telecommunication systems is exploring. Real-time requirements limit the execution time of stereo-vision techniques to 40-60 milliseconds. Classical belief propagation algorithms (BP) generate high quality depth maps. However, the huge number of required memory accesses limits their applicability in real systems. This paper proposes a real-time (latency inferior to 40 millisenconds) high-definition (1280x720) stereo matching algorithm using belief propagation. There are two main contributions. The first one is an improved BP algorithm with occlusion, potential errors and texture-less handling that outperforms classical multi-grid bipartite-graph BP while reducing the number of memory accesses. The second one is an adaptive message compression technique with low performance penalty that greatly reduces the memory traffic. The combination of these techniques outperforms classical BP by about 6.0% while reducing the memory traffic by more than 90%.

关键词： Stereo-vision Belief propagation High-Definition Real-Time FPGA

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X-ray image denoising with directional support value transform

X-ray image denoising with directional support value transfo...

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mippr 2009 - Medical Imaging, Parallel Processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Zheng, Sheng Hendriks, Emile A. Lei, Bangjun Hao, Wei Institute of Intelligent Vision and Image Information China Three Gorges University Yichang 443002 China Information and Communication Theory Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology 2628CD Delft Netherlands

ISBN: (纸本)9780819478085

Under the support vector machine framework, the support value analysis-based image fusion has been studied, where the salient features of the original images are represented by their support values. The support value transform (SVT)-based image fusion approach have demonstrated some advantages over the existing methods in multisource image fusion. In this paper, the directional support value transform (DSVT) is applied to the denoising of some standard images embedded in white noise and the X-ray images. This directional transform is not norm-preserving and, therefore, the variance of the noisy support values will depend on the scales. And then we use the hard-thresholding rule for estimating the unknown support values in different scales and the thresholding is scale-dependent. The peak signal noise ratio (PSNR) is used as an "objective" measure of performance, and our own visual capabilities are used to identify artifacts whose effects may not be well-quantified by the PSNR value. The experimental results demonstrate that simple thresholding of the support values in the proposed method is very competitive with techniques based on wavelets, including thresholding of decimated or undecimated wavelet transforms. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image fusion

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