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IEEE International Conference on Image Processing

作者： Peng-peng Zhang Sheng-zheng Wang Yu Qiao Jie Yang Yong-hui Gao The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China 200240 Merchant Marine College Shanghai Maritime University China 200235

ISBN: (纸本)9781479923427

This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.

关键词： affine soft assignment bidirectional distance point matching In-law Affine transformation Bidirectional Affine Registration observational data iterative methods

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Fine-grained image classification using color exemplar classifiers

Fine-grained image classification using color exemplar class...

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14th Pacific-Rim Conference on Multimedia, PCM 2013

作者： Zhang, Chunjie Xiong, Wei Liu, Jing Zhang, Yifan Liang, Chao Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences P.O. Box 2728 Beijing China National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783319037301

The use of local features has demonstrated its effectiveness for many visual applications. However, local features are often extracted with gray images. This ignores the useful information within different color channels which eventually hinders the final performance, especially for fine-grained image classification. Besides, the semantic information of local features is too weak to be applied for high-level visual applications. To cope with these problems, in this paper, we propose a novel fine-grained image classification method by using color exemplar classifiers. For each image, we first decompose it into multiple color channels to take advantage of the color information. For each color channel, we represent each image with a response histogram which is generated by exemplar classifiers. Experiments on several public image datasets demonstrate the effectiveness of the proposed color exemplar classifier based image classification method. © Springer International Publishing Switzerland 2013.

关键词： Image classification

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Beyond bag of words: Image representation in sub-semantic space 13

Beyond bag of words: Image representation in sub-semantic sp...

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21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Wang, Shuhui Liang, Chao Liu, Jing Huang, Qingming Li, Haojie Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China School of Software Dalian University of Technology Liaoning China Department of Computer Sciences University of Texas San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

Due to the semantic gap, the low-level features are not able to semantically represent images well. Besides, traditional semantic related image representation may not be able to cope with large inter class variations and are not very ro- bust to noise. To solve these problems, in this paper, we propose a novel image representation method in the sub- semantic space. First, examplar classifiers are trained by separating each training image from the others and serve as the weak semantic similarity measurement. Then a graph is constructed by combining the visual similarity and weak se- mantic similarity of these training images. We partition this graph into visually and semantically similar sub-sets. Each sub-set of images are then used to train classifiers in order to separate this sub-set from the others. The learned sub-set classifiers are then used to construct a sub-semantic space based representation of images. This sub-semantic space is not only more semantically meaningful but also more reli- Able and resistant to noise. Finally, we make categorization of images using this sub-semantic space based representation on several public datasets to demonstrate the e®ectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Image representation

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Undo the codebook bias by linear transformation for visual applications 13

Undo the codebook bias by linear transformation for visual a...

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21st ACM International Conference on Multimedia, MM 2013

作者： Zhang, Chunjie Zhang, Yifan Wang, Shuhui Pang, Junbiao Liang, Chao Huang, Qingming Tian, Qi School of Computer and Control Engineering University of Chinese Academy of Sciences 100049 Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Intell. Info. Process Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Science and Technology Beijing University of Technology 100124 Beijing China School of Computer National Engineering Research Center for Multimedia Software Wuhan University 430072 Wuhan China Department of Computer Sciences University of Texas at San Antonio San Antonio TX 78249 United States

ISBN: (纸本)9781450324045

The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the corresponding codebook, the elements of a codebook are viewed as visual words. The local features within each image are then encoded to get the final histogram representation. However, the codebook is dataset dependent and has to be generated for each image dataset. This costs a lot of computational time and weakens the generalization power of the BoW model. To solve these problems, in this paper, we propose to undo the dataset bias by codebook linear transformation. To represent every points within the local feature space using Euclidean distance, the number of bases should be no less than the space dimensions. Hence, each codebook can be viewed as a linear transformation of these bases. In this way, we can transform the pre-learned codebooks for a new dataset. However, not all of the visual words are equally important for the new dataset, it would be more effective if we can make some selection using sparsity constraints and choose the most discriminative visual words for transformation. We propose an alternative optimization algorithm to jointly search for the optimal linear transformation matrixes and the encoding parameters. Image classification experimental results on several image datasets show the effectiveness of the proposed method. Copyright © 2013 ACM.

关键词： Linear transformations

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Fitting a functional structural plant model based on global sensitivity analysis

Fitting a functional structural plant model based on global ...

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2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

作者： Lin, Yubin Kang, Mengzhen Hua, Jing National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467304283

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysis method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs. © 2012 IEEE.

关键词： Sensitivity analysis

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A REVIEW ON ARTERY WALL SEGMENTATION TECHNIQUES AND INTIMA-MEDIA THICKNESS MEASUREMENT FOR CAROTID ULTRASOUND IMAGES

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Journal of Innovative Optical Health Sciences 2012年第1期5卷 75-84页

作者： XIN YANG WANJI HE KAITONG LI JIAOYING JIN XUMING ZHANG MING YUCHI MINGYUE DING State Key Laboratory for Multi-Spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI)Huazhong University of Science and Technology Wuhan 430074HubeiChina Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074HubeiChina

Stroke and heart attack,which could be led by a kind of cerebrovascular and cardiovascular disease named as atherosclerosis,would seriously cause human morbidity and *** is important for the early stage diagnosis and monitoring medical intervention of the *** stenosis is a classical atherosclerotic lesion with vessel wall narrowing down and accumulating plaques *** carotid artery of intima-media thickness(IMT)is a key indicator to the *** the development of computer assisted diagnosis technology,the imaging techniques,segmentation algorithms,measurement methods,and evaluation tools have made considerable *** imaging,being real-time,economic,reliable,and safe,now seems to become a standard in vascular assessment methodology especially for the measurement of *** review firstly attempts to discuss the clinical relevance of measurements in clinical practice at first,and then followed by the challenges that one has to face when approaching the segmentation of ultrasound ***,the commonly used methods for the IMT segmentation and measurement are ***,discussion and evaluation of different segmentation techniques are *** overview of summary and future perspectives is given finally.

关键词： Ultrasound(US)images carotid artery intima-media thickness(IMT) atherosclerosis image segmentation computer assisted diagnosis(CAD)

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Comparison of the camera calibration between photogrammetry and computer vision

Comparison of the camera calibration between photogrammetry ...

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2012 International Conference on System Science and Engineering, ICSSE 2012

作者： Wang, Haixia Shen, Shuhan Lu, Xiao National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Laboratory for Robot and Intelligent Technology of Shandong Province Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781467309455

At present, the camera with high resolution has been widely used. However, it is not accurate for the above camera to use the traditional computer vision method for calibration. So, a method for camera calibration in photogrametry is referred to, and the comparison of the coordinate system, parameter definitions and the camera model between in photogrametry and in computer vision is presented. Thus, the calibration result of photogrametry can be transplanted well to computer vision. Finally, 5DmarkII is used as an example, and its calibration result in the photogrametry is verified by OpenCV functions. © 2012 IEEE.

关键词： Computer vision

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An intelligent framework for plotting using functions

An intelligent framework for plotting using functions

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2012 International Conference on Computer Science and Service System, CSSS 2012

作者： Pan, Feng Guizhou Key Lab of Pattern Recognition and Intelligent Control Guizhou University for Nationalities 550025 Guiyang China School of Computer and Information Engineering Guizhou University for Nationalities 550025 Guiyang China

ISBN: (纸本)9780769547190

In view of the complexity of function mapping coding and the uncertainty of function, this paper proposes that function equation should be separated from the algorithm to design an input program, and then multiple software tools could be utilized to accomplish the complex tasks. This program regards the code generator as the center to dynamically generate graphics code and then calls the execution engine to operate the drawing program. Code generator can automatically generate code for the graphics requirements of any function, which provides a unified mapping framework for the class model of function. The results show that the program is effective and feasible. © 2012 IEEE.

关键词： Mapping

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Detection of billet character in complex production line scene

Detection of billet character in complex production line sce...

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2012 3rd International Conference on Digital Manufacturing and Automation, ICDMA 2012

作者： Hong, Hanyu Yu, Zhejun Zhang, Xiuhua Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430205 China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769547725

Character information is hard to detect in billet scene images by CCD camera. In this paper, we present a method for detection of billet characters from measurements of recursive segmented image. This recursive segmented method can be used in a wide variety of billet scenes. According to high temperature and complex scene in the rolling line, we use an effective clustering and projection characteristics to determine the terminal condition of recursive segmentation. Then we can label character candidate regions in turn by this effective characteristics, and select the regions we want to achieve. The experiments show that this method makes full use of the characteristics of region and clustering. It can improve the quality of detection, and the detection result meets the need of practical application. © 2012 IEEE.

关键词： CCD cameras

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Integrating segmentation and classification accuracy for accuracy assessment in object-based image analysis

Integrating segmentation and classification accuracy for acc...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image Processing, ICALIP 2012

作者： Li, Nan Huo, Hong Fang, Tao Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

ISBN: (纸本)9781467301718

An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relationship between pixels and their corresponding segments according to the overlaps of segments and reference polygons. Then, two improved confusion matrices that take the segmentation errors into consideration are used: one for pixel-level classification results, and the other for object-level classification results. A final accuracy assessment combines the statistics of these two confusion matrices. The proposed method can be applied to segmentation scale selection in the hierarchical interpretation system. An experiment on a SPOT5 image demonstrates the effectiveness of this method for segmentation scale selection, which can guide the fusion of objects of different scales to obtain a higher accuracy. © 2012 IEEE.

关键词： Image analysis

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