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2011 Sixth International Conference on Image and Graphics最新文献

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Efficient Image Denoising by MRF Approximation with Uniform-Sampled Multi-spanning-tree 基于等采样多生成树的MRF近似有效图像去噪
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.186
Jun Sun, Hongdong Li, Xuming He
{"title":"Efficient Image Denoising by MRF Approximation with Uniform-Sampled Multi-spanning-tree","authors":"Jun Sun, Hongdong Li, Xuming He","doi":"10.1109/ICIG.2011.186","DOIUrl":"https://doi.org/10.1109/ICIG.2011.186","url":null,"abstract":"Traditionally, image processing based on Markov Random Field (MRF) is often addressed on a 4-connected grid graph defined on the image. This structure is not computationally efficient. In our work, we develop a multiple-trees structure to approximate the 4-connected grid. A set of spanning trees are generated by a new algorithm: re -- weighted random walk (RWRW). This structure effectively covers the original grid and guarantees uniformly distributed occurrence of each edge. Exact maximum a posterior (MAP) inference is performed on each tree structure by dynamic programming and a median filter is chosen to merge the results together. As an important application, image denoising is used to validate our method. Experimentally, our algorithm provides better performance and higher computational efficiency than traditional methods (such as Loopy Belief Propagation) on a 4-connected MRF.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123320392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Motion Capture of Hand Movements Using Stereo Vision for Minimally Invasive Vascular Interventions 用立体视觉进行微创血管干预的手部运动捕捉
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.125
Dongjin Huang, Wen Tang, Youdong Ding, T. Wan, Xuechun Wu, Yimin Chen
{"title":"Motion Capture of Hand Movements Using Stereo Vision for Minimally Invasive Vascular Interventions","authors":"Dongjin Huang, Wen Tang, Youdong Ding, T. Wan, Xuechun Wu, Yimin Chen","doi":"10.1109/ICIG.2011.125","DOIUrl":"https://doi.org/10.1109/ICIG.2011.125","url":null,"abstract":"A virtual reality (VR) based training system for Minimally Invasive Vascular Surgery can be a very useful training tool for improving skills and reducing errors in operation. Computer vision techniques have the potential to be incorporated into a VR based training system for developing low cost, high accuracy and flexible systems in this area. In this paper, we present an interactive 3D training system that uses stereo vision to capture hand movements as the input operations for the system. The standard operations i.e. pushing, pulling and twisting are captured with stereo vision based on the improved Camshift tracking algorithm and parallel alignment model theory to acquire hand gestures information. We present a new approach to calculate virtual pushing/pulling force and turning angle as extra inputs for understanding these essential operations. In addition, an algorithm that enables the simulator to model guide wire and catheter insertions realistically is presented through these basic actions. The experiment results demonstrate that stereo vision based training system is useful and effective for simulating guide wire insertion procedures with low system cost and flexible operations.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115893227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Video Reshuffling with Narratives toward Effective Video Browsing 视频重组与叙事走向有效的视频浏览
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.49
Wei Fu, Jinqiao Wang, Xiaobin Zhu, Hanqing Lu, Songde Ma
{"title":"Video Reshuffling with Narratives toward Effective Video Browsing","authors":"Wei Fu, Jinqiao Wang, Xiaobin Zhu, Hanqing Lu, Songde Ma","doi":"10.1109/ICIG.2011.49","DOIUrl":"https://doi.org/10.1109/ICIG.2011.49","url":null,"abstract":"With the rapid increasing of video cameras, large amount of video data everyday brings the problem of video storage and browsing. In this paper, we propose a novel approach to video reshuffling with a group of static images to effectively summarize the video content. Each static image called narrative is generated to depict the behavior of a specific object or a special event. Firstly background subtraction and object tracking are employed to extract the segmentations of moving objects and corresponding trajectories. After that, we apply three sampling rules to optimized select representative object samples from the spatial-temporal object tube and stitch them to the background image by Poisson blending. Experimental results show the promise of the proposed approach.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132015402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Unified Method Based on Wavelet Transform and C-V Model for Crack Segmentation of 3D Industrial CT Images 基于小波变换和C-V模型的三维工业CT图像裂纹分割方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.25
Linghui Liu, Li Zeng, B. Bi
{"title":"A Unified Method Based on Wavelet Transform and C-V Model for Crack Segmentation of 3D Industrial CT Images","authors":"Linghui Liu, Li Zeng, B. Bi","doi":"10.1109/ICIG.2011.25","DOIUrl":"https://doi.org/10.1109/ICIG.2011.25","url":null,"abstract":"Accurate segmentation of cracked body from three-dimensional (3D) industrial Computed Tomography (CT) images is an important step in the process of crack measurement and automatic recognition. In this paper we present a fast method for the segmentation of cracked body. The improved algorithm incorporates wavelet transform and Chan and Vese (C-V) model as key components. The 3D wavelet transform is applied for detecting rough edges. Then region growing is used to find a suitable region which contains cracked body. Based on the resulting volume data, 3D C-V model is used to capture the edges of cracked body. The improved method can locate rough regions by using wavelet modulus maxima, which not only reduces the amount of data C-V model processed, but also provides initial contour surface that can accelerate the convergence speed of C-V model. Experimental results illustrate our method can accurately detect the cracked surface, as well as give computational savings of segmentation which satisfy the demand of defects detection of industrial CT.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"2 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125312840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A Multiview Approach to Robust Detection in the Presence of Cast Shadows 投影存在下的多视角鲁棒检测方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.180
Ming Xu, J. Ren, Dong-xia Chen, Jeremy S. Smith, Zhechi Liu
{"title":"A Multiview Approach to Robust Detection in the Presence of Cast Shadows","authors":"Ming Xu, J. Ren, Dong-xia Chen, Jeremy S. Smith, Zhechi Liu","doi":"10.1109/ICIG.2011.180","DOIUrl":"https://doi.org/10.1109/ICIG.2011.180","url":null,"abstract":"This paper presents an object detection algorithm using multiple cameras, which is robust in the presence of cast shadows. The information fusion is based on homography mapping of the foreground regions to a top view image. The homography is based on multiple planar planes parallel to the ground plane. Two novel approaches to estimating such homography have been proposed. The results on an open video dataset are demonstrated.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122985692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Visual Saliency Based Aerial Video Summarization by Online Scene Classification 基于视觉显著性的航拍视频在线场景分类摘要
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.43
Jiewei Wang, Yunhong Wang, Zhaoxiang Zhang
{"title":"Visual Saliency Based Aerial Video Summarization by Online Scene Classification","authors":"Jiewei Wang, Yunhong Wang, Zhaoxiang Zhang","doi":"10.1109/ICIG.2011.43","DOIUrl":"https://doi.org/10.1109/ICIG.2011.43","url":null,"abstract":"Compared with traditional video summarization approaches, aerial video summarization is a new and challenging issue for its particular characteristics. Aerial video data is a massive data stream, without pre-edit structures such as sports or news video data, lack of camera motion such as zoom and pan. On account of these characteristics, we proposed a novel approach for summarization. First, we extract GIST features for each frame as the holistic scene representation. Then, we divide aerial video into temporal segments representing a visual scene using on-line clustering method by examine GIST features of each frame only once. Finally, we select several key frames from each scene for summarization according to visual saliency index (VSI) of each frame computed from their visual saliency map. In the paper, we proposed new criterion for estimation of temporal segmentation of streaming video. Experimental observations show the success of our approach on aerial video summarization.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128173167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Visual Word Pairs for Similar Image Search 相似图像搜索的视觉词对
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.142
Yuan Li, Xiaochun Cao
{"title":"Visual Word Pairs for Similar Image Search","authors":"Yuan Li, Xiaochun Cao","doi":"10.1109/ICIG.2011.142","DOIUrl":"https://doi.org/10.1109/ICIG.2011.142","url":null,"abstract":"The state-of-the-art large scale image retrieval systems have mainly relied on two seminal works: the SIFT descriptor and bag-of-features (BOF) model. However, with the growth of image dataset, the discriminative power of SIFT descriptors was weakened rapidly when mapped to visual words. In this paper, we present a new approach to generate visual word pairs for image retrieval. Two different descriptors are employed to represent the same interest region, and then a visual word pair is obtained by quantizing the descriptor pair with two independent codebooks. By encoding different types of information of the same region, our approach can effectively boost the matching accuracy of descriptors. We evaluate our approach with INRIA Holidays dataset on a 120K image database, and the experiment results suggest that our approach significantly improved the retrieval performance of BOF model.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114249384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
An Effective Classification Approach for EEG-based BCI System 一种基于脑电图的脑机接口系统分类方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.191
Mingzhao Li, Jing Pan
{"title":"An Effective Classification Approach for EEG-based BCI System","authors":"Mingzhao Li, Jing Pan","doi":"10.1109/ICIG.2011.191","DOIUrl":"https://doi.org/10.1109/ICIG.2011.191","url":null,"abstract":"One way to enhance performance of a BCI system is to improve accuracy of classifier. In this paper we apply two development Adaboost classifiers on the basis of an advanced boosting learning algorithm: AdaboostNN and Gentle Adaboost. AdaboostNN works by training nearest-neighbour weak learner on the resampled weighted training data in each iteration, then the weak hypotheses is linearly combined as the final prediction, while a decision tree classifier is available as the weak learner adopted by Gentle Adaboost. LDA and SVM classification methods are also tested to make a comparison with AdaboostNN and Gentle Adaboost. Besides, influence of the number of CSP filters on classification result is also discussed in this paper. By comparison, we get a conclusion that both of these two classifiers are considered to perform more effectively than LDA and SVM, even when the EEG features get a lower separability between two classes.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115917412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Single-Image Super-Resolution via Sparse Coding Regression 基于稀疏编码回归的单图像超分辨率
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.63
Yilong Tang, Yuan Yuan, Pingkun Yan, Xuelong Li
{"title":"Single-Image Super-Resolution via Sparse Coding Regression","authors":"Yilong Tang, Yuan Yuan, Pingkun Yan, Xuelong Li","doi":"10.1109/ICIG.2011.63","DOIUrl":"https://doi.org/10.1109/ICIG.2011.63","url":null,"abstract":"In this paper, it has been shown that the sparse coding algorithm for single-image super-resolution is equivalent to a linear regression algorithm in the sparse coding space. Following the idea, the sparse coding algorithm are generalized by a novel $L_{2}$-Boosting-based single-resolution super-resolution algorithm which focuses on the relationship between sparse codings corresponding to the low- and high-resolution image patches. The experimental results demonstrate the effectiveness of the proposed algorithm by comparing with other state-of-the-art algorithms.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Multi-focus Image Fusion by Nonsubsampled Shearlet Transform 基于非下采样Shearlet变换的多焦点图像融合
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.37
Yuan Cao, Shutao Li, Jianwen Hu
{"title":"Multi-focus Image Fusion by Nonsubsampled Shearlet Transform","authors":"Yuan Cao, Shutao Li, Jianwen Hu","doi":"10.1109/ICIG.2011.37","DOIUrl":"https://doi.org/10.1109/ICIG.2011.37","url":null,"abstract":"In this paper we introduce the nonsubsampled shear let transform for multi-focus image fusion. In the proposed method, source images are decomposed by nonsubsampled shear let transform firstly. Then the decomposition coefficients are merged according to the given fusion rule. Finally the fused image is reconstructed by inverse nonsubsampled shear let transform. The experimental results over five pairs of registered multi-focus images and one pair of mis-registered multi-focus images demonstrate the superiority of the proposed method.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125049468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 42
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