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SVM based classification of moving objects in video

SVM based classification of moving objects in video

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Sun, Airong Bai, Min Tan, Yihua Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Patter Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

In this paper, a classification method of four moving objects including vehicle, human, motorcycle and bicycle in surveillance video was presented by using machine learning idea. The method can be described as three steps: feature selection, training of Support Vector Machine(SVM) classifier and performance evaluation. Firstly, a feature vector to represent the discriminabilty of an object is described. From the profile of object, the ratio of width to height and trisection ratio of width to height are firstly adopted as the distinct feature. Moreover, we use external rectangle to approximate the object mask, which leads to a feature of rectangle degree standing for the ratio between the area of object to the area of external rectangle. To cope with the invariance to scale, rotation and so on, Hu moment invariants, Fourier descriptor and dispersedness were extracted as another kind of features. Secondly, a multi-class classifier were designed based on two-class SVM. The idea behind the classifier structure is that the multi-class classification can be converted to the combination of two-class classification. For our case, the final classification is the vote result of six twoclass classifier. Thirdly, we determine the precise feature selection by experiments. According to the classification result, we select different features for each two-class classifier. The true positive rate, false positive rate and discriminative index are taken to evaluate the performance of the classifier. Experimental results show that the classifier achieves good classification precision for the real and test data. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

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A flower algorithm for autonomous star identification in space surveillance

A flower algorithm for autonomous star identification in spa...

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Gong, Jiaqi Wu, Lin Gong, Junbin Ma, Jie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

The recent increase of space threats yields the idea of using the existing star trackers to perform surveillance of space objects from space. In the missions, due to the observer attitude dynamics, smearing affects the observed stars on the image in space surveillance. Besides, the reflecting flying space objects or debris as spurious stars affects the attitude determination. These are devastating for most star identification algorithms in star trackers. To resolve the problems, this paper defines a star pattern, called Flower code, which is composed of angular distances and circular angles as the characteristics of the pivot star. The angular distances are used for initial lookup table match. Moreover, the circular angles are used for the cyclic dynamic match between the sensor pattern and the pattern candidates from the initial match. The focus of the results is the evaluation of the influence of the reflecting flying spacecraft or debris as spurious stars and the attitude dynamics of the observer spacecraft, on the performance of the algorithms. A number of experiments are carried out on simulated images. The results demonstrated that the proposed method is efficient and robust. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Stars

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Contour-based multisensor image registration using gradient vector features

Contour-based multisensor image registration using gradient ...

引用

MIPPR 2009 - Automatic Target Recognition and Image Analysis: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Ming, Delie Wang, Mi Gao, Pengfei State Key Laboratory for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

ISBN: (纸本)9780819478061

multi-sensor image registration plays an important role in the automatic targets acquirement (ATA). In this paper, two kinds of new multi-sensor image registration methods based on contour feature are put forward. One is gradient vector correlation coefficient method which is based on contour characteristics of the image, the other is called relative gradient difference method which is in fact a measurement of differences between out-contour area and inner area of the target. Lots of experimental data composed of satellite images and real-time infrared images are used to verify the above two algorithms, and the results show that the two proposed methods can have good performances for both day and night infrared images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image registration

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Combining variable precision rough set and neural network in remote sensing image classification

Combining variable precision rough set and neural network in...

引用

MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Wang, Qiong Liu, Jian IPRAI of HUST State Key Laboratory for Multi-spectral Information Processing Technologies Wuhan 430074 China Mathematics Department of HUST Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper presents a new approach of Remotely Sensed data classification based on Variable Precision Rough set(VPRS) and BP neural network, compared to traditional rough sets, VPRS is more robust to noise and can generate more concise and representative classification rules of the remote sensing image. After the rules are deduced, they are fed to the BP neural network, which results in short training time and a high classification accuracy. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Neural networks

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A framework of passive millimeter-wave imaging simulation for typical ground scenes

A framework of passive millimeter-wave imaging simulation fo...

引用

MIPPR 2009 - multispectral Image Acquisition and processing: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Yan, Luxin Ge, Rui Zhong, Sheng Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478054

Passive millimeter-wave (PMMW) imaging offers advantages over visible and IR imaging in having better all weather performance. However the PMMW imaging sensors are state-of-the-art to date, sometimes it is required to predict and evaluate the performance of a PMMW sensor under a variety of weather, terrain and sensor operational conditions. The PMMW scene simulation is an efficient way. This paper proposes a framework of the PMMW simulation for ground scenes. Commercial scene modeling software, multigen and Vega, are used to generate the multi-viewpoint and multi-scale description for natural ground scenes with visible images. The background and objects in the scene are classified based on perceptive color clusters and mapped with different materials. Further, the radiometric temperature images of the scene are calculated according to millimeter wave phenomenology: atmospheric propagation and emission including sky temperature, weather conditions, and physical temperature. Finally, the simulated output PMMW images are generated by applying the sensor characteristics such as the aperture size, data sample scheme and system noise. Tentative results show the simulation framework can provide reasonable scene's PMMW image with high fidelity. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Infrared imaging

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An FPGA-based histogram equalization implementation

An FPGA-based histogram equalization implementation

引用

MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Li, Yang Zhong, Sheng Wang, Bo Yan, Luxin Liu, Tao Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China National Key Laboratory of Multi-spectral Information Processing Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Image histogram equalization technology is always a very important basic processing technology in image process field. In infrared image processing system, low contrast and shortage of gray levels often make it very difficult to observe and recognize targets. In this situation, Real-time image histogram equalization technology is often used to enhance infrared image contrast, improve infrared image quality and ameliorate image processing system performance. In embedded system, when real-time image histogram equalization is required, it is very difficult for the typical design methods by using general purpose DSP or MCU to meet the real-time requirement. It is a very good choice to choose FPGA hardware logic to implement image histogram equalization. Here in this paper, we introduce an FPGA based image histogram equalization implementation in detail which can meet real-time requirement very well. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image enhancement

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Design and implementation of a scalable enhanced high-performance DMA architecture for complex SoC

Design and implementation of a scalable enhanced high-perfor...

引用

MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Zhao, Hualong Sang, Hongshi Zhang, Tianxu Shen, Xubang State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

As the demand of higher image quality and greater processing capabilities are growing, obtaining higher data bandwidth for on-chip processing is becoming a more and more important issue. DMA (Direct Memory Access) component, as the key element in stream processing SoC (System on Chip) [1], should be deeply researched and designed to satisfy the high data bandwidth requirement of processing units. In this paper, we introduce a scalable high-performance DMA architecture for complex SoC to satisfy rigorous high sustained bandwidth and versatile functionality requirements. Several techniques and structures are proposed in this paper. An integrated verification environment is also built for our design to fully verify its functionality. And the performance improvement by using our architecture is analyzed. At the end of the paper, the post-simulation and tape-out results are provided. The whole implementation has been silicon proven to be functional and efficient. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： System-on-chip

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Curve reconstruction from a set of dense scattered points using A* algorithm

Curve reconstruction from a set of dense scattered points us...

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MIPPR 2009 - Automatic Target Recognition and Image Analysis: 6th International Symposium on multispectral Image processing and Pattern Recognition

作者： Sun, Yangguang Zhou, Chengping Cai, Chao Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies HUST Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China HUST Wuhan 430074 China

ISBN: (纸本)9780819478061

In this paper, a novel curve reconstruction method based on A* algorithm from a set of dense scattered points was proposed. Our method can not only reconstruct dense scattered points with single connected complicated form, but also solve the problem building the curve from the scattered points with close form and multiply connected form. Moreover, the influence of noise points on reconstructed curves is farther decreased, and the shape of dense scattered points will be well hold. Experimental results have demonstrated that the proposed method has the feasibility and robustness. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Pattern recognition

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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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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

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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： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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