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2013 IEEE International Conference on Image Processing最新文献

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Classification of ex-vivo breast cancer positive margins measured by hyperspectral imaging 高光谱成像测量离体乳腺癌阳性边缘的分类
2013 IEEE International Conference on Image Processing Pub Date : 2013-12-01 DOI: 10.1109/ICIP.2013.6738289
Reza Pourreza-Shahri, F. Saki, N. Kehtarnavaz, P. Leboulluec, H. Liu
{"title":"Classification of ex-vivo breast cancer positive margins measured by hyperspectral imaging","authors":"Reza Pourreza-Shahri, F. Saki, N. Kehtarnavaz, P. Leboulluec, H. Liu","doi":"10.1109/ICIP.2013.6738289","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738289","url":null,"abstract":"This paper presents our recent development of a classification algorithm for identification of breast cancer margins measured by hyperspectral imaging for the purpose of lowering the number of missed positive margins in breast cancer lumpectomy. After extracting Fourier coefficient selection features and reducing the dimensionality of hyperspectral image data via the Minimum Redundancy Maximum Relevance method, an SVM classifier involving a radial basis kernel function is deployed to separate cancerous tissues from normal tissues. By examining exvivo breast cancer hyperspectral images tagged by a pathologist, the developed classification approach is shown to achieve a sensitivity of about 98% and a specificity of about 99%.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133727426","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: 19
Novel PCA-based color-to-gray image conversion 一种新的基于pca的彩色到灰度图像转换
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-18 DOI: 10.1109/ICIP.2013.6738470
Ja-Won Seo, Seong-Dae Kim
{"title":"Novel PCA-based color-to-gray image conversion","authors":"Ja-Won Seo, Seong-Dae Kim","doi":"10.1109/ICIP.2013.6738470","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738470","url":null,"abstract":"In this paper, we present a novel color-to-gray image conversion method which preserves both color and texture discriminabilities effectively. Unlike previous approaches, the proposed method does not require any user-specific parameters for conversion. Moreover, the computational complexity is low enough to be applied to real-time applications. These breakthroughs are achieved by applying the ELSSP (Eigenvalue-weighted Linear Sum of Subspace Projections) method, which is proposed in this paper for the color-to-gray image conversion. Experimental results demonstrate that the proposed method is superior to the state-of-the-art methods in terms of both conversion speed and image quality.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131330444","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: 31
Video tracking through occlusions by fast audio source localisation 通过快速音频源定位的闭塞视频跟踪
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-17 DOI: 10.1109/ICIP.2013.6738548
Eleonora D'Arca, Ashley Hughes, N. Robertson, J. Hopgood
{"title":"Video tracking through occlusions by fast audio source localisation","authors":"Eleonora D'Arca, Ashley Hughes, N. Robertson, J. Hopgood","doi":"10.1109/ICIP.2013.6738548","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738548","url":null,"abstract":"In this paper we present a novel audio-visual speaker detection and localisation algorithm. Audio source position estimates are computed by a novel stochastic region contraction (SRC) audio search algorithm for accurate speaker localisation. This audio search algorithm is aided by available video information (stochastic region contraction with height estimation (SRC-HE)) which estimates head heights over the whole scene and gives a speed improvement of 56% over SRC. We finally combine audio and video data in a Kalman filter (KF) which fuses person-position likelihoods and tracks the speaker. Our system is composed of a single video camera and 16 microphones. We validate the approach on the problem of video occlusion i.e. two people having a conversation have to be detected and localised at a distance (as in surveillance scenarios vs. enclosed meeting rooms). We show video occlusion can be resolved and speakers can be correctly detected/localised in real data. Moreover, SRC-HE based joint audio-video (AV) speaker tracking outperforms the one based on the original SRC by 16% and 4% in terms of multi object tracking precision (MOTP) and multi object tracking accuracy (MOTA). Speaker change detection improves by 11% over SRC.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122644536","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: 9
A novel method for salient object detection via compactness measurement 一种基于紧凑度测量的显著目标检测新方法
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-16 DOI: 10.1109/ICIP.2013.6738707
Jiwhan Kim, Han S. Lee, Junmo Kim
{"title":"A novel method for salient object detection via compactness measurement","authors":"Jiwhan Kim, Han S. Lee, Junmo Kim","doi":"10.1109/ICIP.2013.6738707","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738707","url":null,"abstract":"Salient object detection is a process of extracting an object which is visually attractive from a single image or a video. As a powerful technique for automatic image or video segmentation, saliency detection has been focused and studied recently. In this paper, we propose a novel method for salient object detection without training or learning-based techniques. The proposed framework consists of two major steps, the generation of saliency map candidates and the selection of an optimal saliency map. To generate saliency map candidates, prior maps based on combinations of RGB color components are proposed. To select the optimal saliency map among the candidates, we propose a compactness measure, which evaluates the degree to which the generated saliency maps show objects. As a result, among recent works on saliency detection, our saliency detection method achieves the highest performance in terms of saliency detection.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129168109","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
3D shape similarity using vectors of locally aggregated tensors 利用局部聚合张量向量的三维形状相似性
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-16 DOI: 10.1109/ICIP.2013.6738555
Hedi Tabia, David Picard, Hamid Laga, P. Gosselin
{"title":"3D shape similarity using vectors of locally aggregated tensors","authors":"Hedi Tabia, David Picard, Hamid Laga, P. Gosselin","doi":"10.1109/ICIP.2013.6738555","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738555","url":null,"abstract":"In this paper, we present an efficient 3D object retrieval method invariant to scale, orientation and pose. Our approach is based on the dense extraction of discriminative local descriptors extracted from 2D views. We aggregate the descriptors into a single vector signature using tensor products. The similarity between 3D models can then be efficiently computed with a simple dot product. Experiments on the SHREC12 commonly-used benchmark demonstrate that our approach obtains superior performance in searching for generic shapes.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129419945","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: 4
Spatio-temporal segmentation and estimation of ocean surface currents from satellite sea surface temperature fields 基于卫星海面温度场的海流时空分割与估算
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-15 DOI: 10.1109/ICIP.2013.6738483
P. Tandeo, Silèye O. Ba, Ronan Fablet, B. Chapron, E. Autret
{"title":"Spatio-temporal segmentation and estimation of ocean surface currents from satellite sea surface temperature fields","authors":"P. Tandeo, Silèye O. Ba, Ronan Fablet, B. Chapron, E. Autret","doi":"10.1109/ICIP.2013.6738483","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738483","url":null,"abstract":"The use of satellite Sea Surface Temperature (SST) fields to retrieve zonal and meridional surface currents (U, V) is now a widespread idea. Since the classical approach involves temporal differencing of SST fields, we investigate in this paper the extent to which mesoscale ocean dynamics may be decomposed into a superposition of dynamical modes, characterized by different linear relationships between surface currents and temperature fields. Based on a completely observation-driven approach, we propose a latent class regression model from local satellite surface currents and patches of SST measurements. Applied to the highly dynamical Agulhas region, we demonstrate and discuss the geophysical relevance of the proposed mixture model to achieve a spatio-temporal segmentation and tracking of the ocean surface dynamical modes. Moreover, we show the accuracy of the proposed model to predict mesoscale surface currents from SST single maps.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114947615","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
Dual-domain image denoising 双域图像去噪
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-15 DOI: 10.1109/ICIP.2013.6738091
Claude Knaus, Matthias Zwicker
{"title":"Dual-domain image denoising","authors":"Claude Knaus, Matthias Zwicker","doi":"10.1109/ICIP.2013.6738091","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738091","url":null,"abstract":"Image denoising methods have been implemented in both spatial and transform domains. Each domain has its advantages and shortcomings, which can be complemented by each other. State-of-the-art methods like block-matching 3D filtering (BM3D) therefore combine both domains. However, implementation of such methods is not trivial. We offer a hybrid method that is surprisingly easy to implement and yet rivals BM3D in quality.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130310024","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: 119
Salient level lines selection using the Mumford-Shah functional 使用Mumford-Shah函数选择显著水平线
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-15 DOI: 10.1109/ICIP.2013.6738253
Yongchao Xu, T. Géraud, Laurent Najman
{"title":"Salient level lines selection using the Mumford-Shah functional","authors":"Yongchao Xu, T. Géraud, Laurent Najman","doi":"10.1109/ICIP.2013.6738253","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738253","url":null,"abstract":"Many methods relying on the morphological notion of shapes, (i.e., connected components of level sets) have been proved to be very useful for pattern analysis and recognition. Selecting meaningful level lines (boundaries of level sets) yields to simplify images while preserving salient structures. Many image simplification and/or segmentation methods are driven by the optimization of an energy functional, for instance the Mumford-Shah functional. In this article, we propose an efficient shape-based morphological filtering that very quickly compute to a locally (subordinated to the tree of shapes) optimal solution of the piecewise-constant Mumford-Shah functional. Experimental results demonstrate the efficiency, usefulness, and robustness of our method, when applied to image simplification, pre-segmentation, and detection of affine regions with viewpoint changes.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123166463","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: 22
Context-based video coding 基于上下文的视频编码
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-15 DOI: 10.1109/ICIP.2013.6738402
Richard George Vigars, A. Calway, D. Bull
{"title":"Context-based video coding","authors":"Richard George Vigars, A. Calway, D. Bull","doi":"10.1109/ICIP.2013.6738402","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738402","url":null,"abstract":"We present a video CODEC framework which exploits extrinsic scene knowledge to condition a perspective motion model. An approximate textural-geometric model of the scene is prepared prior to coding. During coding, the locations of planar surfaces in the scene are tracked, facilitating the computation of accurate perspective motion warp parameters. These algorithms are integrated with H.264 into a hybrid CODEC framework, achieving savings of up to 48% for equivalent visual quality.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133738194","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
Image classification using object detectors 利用目标检测器进行图像分类
2013 IEEE International Conference on Image Processing Pub Date : 2013-09-15 DOI: 10.1109/ICIP.2013.6738894
Thibaut Durand, Nicolas Thome, M. Cord, S. Avila
{"title":"Image classification using object detectors","authors":"Thibaut Durand, Nicolas Thome, M. Cord, S. Avila","doi":"10.1109/ICIP.2013.6738894","DOIUrl":"https://doi.org/10.1109/ICIP.2013.6738894","url":null,"abstract":"Image categorization is one of the most competitive topic in computer vision and image processing. In this paper, we propose to use trained object and region detectors to represent the visual content of each image. Compared to similar methods found in the literature, our method encompasses two main areas of novelty: introducing a new spatial pooling formalism and designing a late fusion strategy for combining our representation with state-of-the art methods based on low-level descriptors, e.g. Fisher Vectors and BossaNova. Our experiments carried out in the challenging PASCAL VOC 2007 dataset reveal outstanding performances. When combined with low-level representations, we reach more than 67.6% in MAP, outperforming recently reported results in this dataset with a large margin.","PeriodicalId":388385,"journal":{"name":"2013 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129146110","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
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