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An adaptive mean shift algorithm based on LSH

An adaptive mean shift algorithm based on LSH

引用

2011 International Conference on Power Electronics and Engineering Application

作者： Yanbin Cui Kui Cao Gang Zheng Fan Zhang College of Computer and Information Engineering Henan University Institute of Image Processing and Pattern Recognition Henan University

The time complexity of the adaptive mean shift is related to the dimension of data and the number of iterations. The computational complexity will increase proportionally with the increase of the data dimension. An approximate neighborhood queries method is presented for the computation of high dimensional data, in which, the localitysensitive hashing(LSH) is used to reduce the computational complexity of the adaptive mean shift algorithm. Experimental results show that the proposed algorithm can reduce the complexity of the adaptive mean shift algorithm and can produce a more accurate classification than the fixed bandwidth mean shift algorithm.

关键词： pattern Classification Adaptive bandwidth Adaptive mean-shift Locality-sensitive hashing

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Shape deformation using golden section search in PCA-based statistical shape model

Shape deformation using golden section search in PCA-based s...

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作者： Liu, W.P. Shang, Y.F. Yang, X. Deklerck, R. Cornelis, J. Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Dong Chuan Rd. 800 Shang Hai China Department of Electronics and Informatics Vrije Universiteit Brussel Brussel Belgium Institute of Broad Band Technology Gaston Crommenlaan Gent Belgium

An effective shape deformation method derived from a PCA-based statistical shape model (SSM) using the Golden Section Search (GSS) method is presented. The PCA-based SSM has proved to be a simple and effective method in model based segmentation and has been used in medical image analysis for soft tissue extraction. The gradient descent method is widely applied to search the optimal values for the transformation and deformation parameters to fit the model to specific image features. We use Golden Section Search instead, yielding some conceptual advantages, and experimentally illustrated good performance as well as lower execution times compared to gradient descent methods. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： image segmentation

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Interactive object segmentation using iterative adjustable graph cut

Interactive object segmentation using iterative adjustable g...

引用

2011 IEEE Visual Communications and image processing, VCIP 2011

作者： Shi, Ran Liu, Zhi Xue, Yinzhu Zhang, Xiang School of Communication and Information Engineering Shanghai University Shanghai 200072 China Key Laboratory of Advanced Display and System Application Shanghai University Ministry of Education Shanghai 200072 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9781457713200

Interactive object segmentation is widely used for extracting any user-interested objects from natural images. A common problem with many interactive segmentation approaches is that the object segmentation quality is degraded due to inaccurate object/background seeds provided by the user. This paper proposes an iterative adjustable graph cut to efficiently solve this problem. First, object/background seeds are initialized based on the object segmentation result obtained with the user-specified scribbles as the interactive input. Then, an iterative seed adjustment scheme is exploited to correct inaccurate seeds and extract new suitable seeds via graph cut, in which the balancing weight between energy terms are adaptively updated to protect stable seeds and speedup the iteration process. Finally, suitable seeds are obtained and graph cut is used to segment the objects. Experimental results demonstrate the better segmentation performance of our approach even if user provides rather rough seeds. © 2011 IEEE.

关键词： image segmentation

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VIDEO OBJECT TRACKING WITH DIFFERENTIAL STRUCTURAL SIMILARITY INDEX

VIDEO OBJECT TRACKING WITH DIFFERENTIAL STRUCTURAL SIMILARIT...

引用

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Artur Loza Fanglin Wang Jie Yang Lyudmila Mihaylova Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Computing and Communications Lancaster University UK

ISBN: (纸本)9781457705380

The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared with similar methods based on colour and edge histograms and Bhattacharyya distance. However, the combined use of the structural similarity and a particle filter results in increased computational complexity of the algorithm. In this paper, a novel fast approach for video tracking based on the structural similarity measure is presented. The tracking algorithm proposed determines the state of the target (location, size) based on the gradient ascent procedure applied to the structural similarity surface of the video frame, thus avoiding computationally expensive sampling of the state space. The new method, while being computationally less expensive, has shown higher accuracy compared with the standard mean shift algorithm and the SSIM Particle Filter (SSIM-PF) [1] and its performance is illustrated over real video sequences.

关键词： Tracking structural similarity gradient ascent tracking similar measure Videotapes Video object Particle filters complexity classes state space

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Prediction of Protein Quaternary Structure by a Novel Manifold Learning Algorithm

Prediction of Protein Quaternary Structure by a Novel Manifo...

引用

International Workshop on Intelligent Systems and Applications, ISA

作者： Tong Wang Jian Wang Lixiu Yao Institute of Computer and Information Shanghai Second Polytechnic University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

With the explosion of protein sequences generated in the Post-Genomic Age, it is urgent to develop an automated method to predict protein quaternary structure. To explore this problem, we adopted an approach based on a sequence encoding descriptor by fusing PseAA (Pseudo Amino Acid) and DC (Dipeptide Composition) representing a protein sample. Here, a completely different approach, manifold learning algorithm MVP (Maximum variance projection) is introduced to extract the key features from the high-dimensional feature space. The dimension-reduced descriptor vector thus obtained is a compact representation of the original high dimensional vector. Our jackknife test results indicate that it is very promising to use the dimensionality reduction approaches to cope with complicated problems in biological systems, such as predicting the quaternary structure of proteins.

关键词： Proteins Amino acids Feature extraction Prediction algorithms Classification algorithms Support vector machine classification Biological systems

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Soft subspace clustering with competitive agglomeration

Soft subspace clustering with competitive agglomeration

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Lin Zhu Longbing Cao Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Faculty of Engineering and IT QCIS Sydney University of Technology Sydney Australia

In this paper, two novel soft subspace clustering algorithms, namely fuzzy weighting subspace clustering with competitive agglomeration (FWSCA) and entropy weighting subspace clustering with competitive agglomeration (EWSCA), are proposed to overcome the problems of the unknown number of clusters and the initialization of prototypes for soft subspace clustering. The main advantage of FWSCA and EWSCA lies in the fact that they effectively integrate the merits of soft subspace clustering and the good properties of fuzzy clustering with competitive agglomeration. This makes it possible to obtain the appropriate number of clusters during the clustering progress. Moreover, FWSCA and EWSCA algorithms can converge regardless of the initial number of clusters and initialization. Substantial experimental results on both synthetic and real data sets demonstrate the effectiveness of FWSCA and EWSCA in addressing the two problems.

关键词： Clustering algorithms Entropy Partitioning algorithms Equations Prototypes Electronic mail Indexes

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The influence of hubness on nearest-neighbor methods in object recognition

The influence of hubness on nearest-neighbor methods in obje...

引用

IEEE International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Nenad Tomašev Raluca Brehar Dunja Mladenić Sergiu Nedevschi Jožef Stefan Institute Artificial Intelligence Laboratory Ljubljana Slovenia Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania

Object recognition from images is one of the essential problems in automatic image processing. In this paper we focus specifically on nearest neighbor methods, which are widely used in many practical applications, not necessarily related to image data. It has recently come to attention that high dimensional data also exhibit high hubness, which essentially means that some very influential data points appear and these points are referred to as hubs. Unsurprisingly, hubs play a very important role in the nearest neighbor classification. We examine the hubness of various image data sets, under several different feature representations. We also show that it is possible to exploit the observed hubness and improve the recognition accuracy.

关键词： Feature extraction Object recognition Entropy Histograms Visualization image color analysis Shape

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Perceptual prediction for bionically inspired autonomous agents

Perceptual prediction for bionically inspired autonomous age...

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AFRICON Conference

作者： Clemens Muchitsch Alexander Wendt Klaus Doblhammer Dietmar Bruckner Jana Machajdik Institute of Computer Technology Vienna University of Technology Vienna Austria Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria

To manage the increasing volume of data per time unit, achievements in information processing and artificial intelligence were made. But still the complex processes of human perception and scenario recognition are not fully understood and still far from implementation in technical applications. The contribution of this article to the field of cognitive automation is the concept of prediction for perceptual- and scenario-recognition frameworks. It is a model where prediction originates from neuro-psychoanalytical theories. Inspired by experience-based planning, which is used by the psychoanalytical decision unit, the prediction of possible outcomes from scenarios can be used for proactive acting. It results in a higher detection rate and a faster performance for recognition-units. This first implementation shows the possibilities of the concept and gives an outlook of the performance as soon as the system is fully integrated in the decision-unit.

关键词： Humans Knowledge based systems Conferences TV Educational institutions Brain modeling Decision making

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Improved coherence-enhancing diffusion with hybrid diffusion tensor

Improved coherence-enhancing diffusion with hybrid diffusion...

引用

International Conference on Multimedia Technology

作者： Xiaoguang Chen Xiaolan Du Zhongnan Lv Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China Center of Computer and Network Management North-China University of Technology Beijing China

Coherence-enhancing diffusion (CED), based on analysis of oriented structures, has been extensively used in image processing. This diffusion filtering can keep some junctions and close broken linear structures, but it also destroys crease points and deforms nonlinear structures. In this paper, we proposed an improved algorithm for CED based on analysis of structure tensor and Hessian matrix. This approach can not only denoise and enhance linear structures such as edges, but also preserve nonlinear structures such as creases. Experiments with fingerprint image show that the improved CED outperforms classical CED.

关键词： Tensile stress image edge detection Junctions Fingerprint recognition Algorithm design and analysis Coherence Filtering

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

引用

Conference on Computer Vision and pattern recognition (CVPR)

作者： Xiaogang Chen Xiangjian He Jie Yang Qiang Wu Key Laboratory of System Control and Information Processing Ministry of Education China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Centre of Innovation in IT Services and Applications University of Technology Sydney Australia

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method.

关键词： image restoration Histograms TV Object segmentation Deconvolution Estimation image segmentation

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