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3D space-time detection based control points selection of DSA

3D space-time detection based control points selection of DS...

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2010 2nd Pacific-Asia Conference on Circuits, Communications and System, PACCS 2010

作者： Zhang, Fan Li, Bo Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China

ISBN: (纸本)9781424479689

A 3D space-time motion detection based DSA control point selection algorithm is proposed. Main content is to detect the movement of image points based on the control selection and registration algorithm and using DSA image sequences to speed up the registration of control points. The image features, such as the edge, are used as the control points to register image effectively. According to the location of control points, 3D space-time characteristics are used to search control points, and it will further reduce the number of control points, and make the control point registration more accurate. © 2010 IEEE.

关键词： 3D space-time characteristics 3D space-time detection 3D space-time detection 3D space-time motion detection DSA control point selection algorithm DSA image sequences control point registration control points control points registration control points selection control selection diagnostic radiography digital subtraction angiography image features image points image registration image registration image sequences medical image processing motion compensation registration algorithm

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A hole filling algorithm for medical imaging

A hole filling algorithm for medical imaging

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International Conference on Information Science and Engineering (ICISE)

作者： Lv Guo Yonghui Gao Yin Li Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Surface integrity of 3D medical imaging is crucial for surgery simulation or virtual diagnoses. However, undesirable holes often exist due to external damage on bodies or accessibility limitation on scanners. To bridge the gap, the paper proposes an algorithm of filling holes for 3D medical image data based on moving least squares (MLS) method. In the algorithm, medical data is classified into two types and procedure is designed according to the classification. The procedure consists of two steps, namely hole detection and hole completion. In completion part, the detected hole can be automatically filled by interpolation with known surrounding points. Moreover, a threshold is used to constrain the density of the completed surface, so the sampling rate on reconstructed area complies with the original data. We test our algorithm on two types of medical data and the results indicate a robust solution.

关键词： Filling Three dimensional displays Surface reconstruction Medical diagnostic imaging Arrays image reconstruction

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Model-based 3D human motion tracking and voxel reconstruction from sparse views

Model-based 3D human motion tracking and voxel reconstructio...

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IEEE International Conference on image processing

作者： Junchi Yan Jian Song Liwei Wang Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper addresses a method for 3D human motion tracking and voxel-based reconstruction from sparse views. We adopt the annealed Gaussian based particle swarm optimization (AGPSO) for 3D human motion tracking. The AGPSO algorithm incorporates the temporal continuity information into the traditional particle swarm optimization (PSO) algorithm under a Bayesian framework. In the online tracking process, the state variables are estimated via the particle filtering, where the observation is designed as a minimized Markov Random Field (MRF) energy. Finally, voxel reconstruction is conducted using the skeleton shape prior via dynamic graph cut. The experimental results show that our method performs promisingly against the cluttered background and generates plausible voxel reconstructions from sparse views.

关键词： Three dimensional displays Tracking Humans image reconstruction Shape Skeleton Annealing

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Head Pose Estimation from Low-Resolution image with Hough Forest

Head Pose Estimation from Low-Resolution Image with Hough Fo...

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Chinese Conference on pattern recognition (CCPR)

作者： Ming Zhang Ke Li Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

An approach for head pose estimation has been proposed in this paper using Hough forest. The estimation of pose are generated by voting from image patches as in a Hough transform. The basic idea is that image patches which contain eyes, hair or neck can give rich information about the head position and orientation. The voting process is implemented by randomized forest which is an efficient and robust tool for classification and regression. The method is quantitatively evaluated by comparing the estimated pose to the ground truth.

关键词： Head Estimation Training Uncertainty Humans Target tracking Computer vision

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A hybrid image representation for indoor scene classification

A hybrid image representation for indoor scene classificatio...

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International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Zhibin Niu Yue Zhou Kun Shi Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424496297

Although scene classification has been studied for decades, indoor scene recognition remains challenging due to its large view point variance and massive irregular artefacts. In fact, most existing methods for outdoor scene classification perform poorly in the indoor situation. To address the problem, we propose a hybrid image representation by combining the global information with the local structure of the scene. First, the global discriminative information is captured by pyramid GIST feature. Second, the local structure is encoded by the bag of features method with Histogram Intersection Kernel (HIK). Finally, HIK based SVM is employed for learning and classification. Experiments on the MIT indoor scene database show that our approach could significantly improve the recognition accuracy of the state-of-art methods by about 14%.

关键词： Support vector machines

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Conotoxin Superfamily Prediction Based on Diffusion Maps and dHKNN

Conotoxin Superfamily Prediction Based on Diffusion Maps and...

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Chinese Conference on pattern recognition (CCPR)

作者： Jiang-Bo Yin Jian-Bo Lei Yong-Xian Fan Hong-Bin Shen Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

Conotoxins show prospects for being potent pharmaceuticals in the treatment of some serious disease. Accurate prediction of conotoxin superfamily would have many important applications in biological research and clinical medicine. In this study, we propose a novel dHKNN method to predict conotoxin superfamily. Firstly, we extract the protein's sequential features composed of physicochemical properties, evolutionary information, predicted secondary structures and amino acid composition. Then we use the diffusion maps for dimensionality *** last, with considering the local density information in the diffusion space, the dHKNN is proposed based on the K-local hyperplane distance nearest neighbor subspace classifier method for predicting conotoxin superfamilies. An overall accuracy of 91.90% is obtained through the jackknife cross-validation test which is higher than present methods.

关键词： Proteins Bioinformatics Amino acids Accuracy Databases Gene expression

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Projection correlation based noise reduction in volume CT

Projection correlation based noise reduction in volume CT

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Hao Yan Xuanqin Mou Institute of Image Processing and Pattern Recognition Xi''an Jiaotong University Xi'an China

De-noising algorithms for volume CT are proposed based on the correlation of the cone beam (CB) CT projections. The main idea is: when the correlated pixels among the neighboring views are added together according to this projection correlation (PC), the signal will be retained, whereas the noise variance upon them will be reduced by this averaging process, because the signal obeys this correlation but noise not. PC based filtering (PCF) method is developed. PCF is further integrated as PC based penalty weighted least square (PC-PWLS) method. Validations are performed for two volume scans: one is ideal low-dose case, and the other considers the high-frequency scatter residues after scatter correction. By using the proposed methods, significant noise suppressing is illustrated; meanwhile, the spatial resolution can be well preserved. For the low dose scan, SNR (Signal to Noise Ratio) increases are around 14 dB. For the cone beam scan with high frequency scatter residues, an effect approaching to the fan-beam scan is achieved.

关键词： Pixel Noise measurement Computed tomography Noise reduction Correlation Signal to noise ratio

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A Bayesian framework for 3D human motion tracking from monocular image

A Bayesian framework for 3D human motion tracking from monoc...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Jian Liu Junchi Yan Minglei Tong Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper addresses a strategy for 3D human motion recovery from monocular image. We advocate the use of Gaussian Process Dynamical Model (GPDM) for learning human pose and motion priors for 3D people tracking. With the prior learned from GPDM, we integrate our approach into a Bayesian tracking framework of condensation. During the off-line training step, a GPDM provides the reversible mappings between low-dimensional latent space and high-dimensional pose space, and then in the online tracking process, the latent variables are estimated via the particle filtering, and the observation is designed as a energy function based on a Markov Random Field (MRF) theory. The proposed approach is demonstrated on our database, and the experimental results show that our method performs promisingly.

关键词： Humans Three dimensional displays Tracking Shape image reconstruction Pixel Bayesian methods

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Visual saliency detection via rank-sparsity decomposition

Visual saliency detection via rank-sparsity decomposition

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IEEE International Conference on image processing

作者： Junchi Yan Jian Liu Yin Li Zhibin Niu Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Saliency mechanism has been considered crucial in the human visual system and helpful to object detection and recognition. This paper addresses a novel feature-based model for visual saliency detection. It consists of two steps: first, using the learned overcomplete sparse bases to represent image patches; and then, estimating saliency information via direct low-rank and sparsity matrix decomposition. We compare our model with the previous methods on natural images. Experimental results show that our model performs competitively for visual saliency detection task, and suggest the potential application of matrix decomposition and convex optimization for image analysis.

关键词： Matrix decomposition Sparse matrices Visualization Dictionaries Humans Convex functions Encoding

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Research on Fuzzy C Switching Regression Model with Generalized Improved Fuzzy Partitions

Research on Fuzzy C Switching Regression Model with Generali...

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Chinese Conference on pattern recognition (CCPR)

作者： Beibei Qin Lin Zhu Jie Yang Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

By introducing a novel membership constraint function, a new algorithm called fuzzy c-means switching regression model with generalized improved fuzzy partitions (GIFP-FCRM) is proposed. This algorithm seems less sensitive to noise and outliers than the classical fuzzy C switching regression model (FCRM), and provides a generalized model with the fuzziness index m for the fuzzy C switching regression model with improved fuzzy partitions (IFP-FCRM). Furthermore, with fuzzy parameter α, the classical FCRM and IFP-FCRM can be taken as two special cases of the proposed algorithm. Several experimental results are presented to demonstrate its advantage over FCRM in both noise insensitivity and robustness capability.

关键词： Switches Partitioning algorithms Clustering algorithms pattern recognition Biological system modeling image processing Artificial intelligence

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