2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops最新文献_第9页

Automatic symmetry-integrated brain injury detection in MRI sequences MRI序列中对称性集成脑损伤自动检测

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204052

Yu Sun, B. Bhanu, Shiv Bhanu

{"title":"Automatic symmetry-integrated brain injury detection in MRI sequences","authors":"Yu Sun, B. Bhanu, Shiv Bhanu","doi":"10.1109/CVPRW.2009.5204052","DOIUrl":"https://doi.org/10.1109/CVPRW.2009.5204052","url":null,"abstract":"This paper presents a fully automated symmetry-integrated brain injury detection method for magnetic resonance imaging (MRI) sequences. One of the limitations of current injury detection methods often involves a large amount of training data or a prior model that is only applicable to a limited domain of brain slices, with low computational efficiency and robustness. Our proposed approach can detect injuries from a wide variety of brain images since it makes use of symmetry as a dominant feature, and does not rely on any prior models and training phases. The approach consists of the following steps: (a) symmetry integrated segmentation of brain slices based on symmetry affinity matrix, (b) computation of kurtosis and skewness of symmetry affinity matrix to find potential asymmetric regions, (c) clustering of the pixels in symmetry affinity matrix using a 3D relaxation algorithm, (d) fusion of the results of (b) and (c) to obtain refined asymmetric regions, (e) Gaussian mixture model for unsupervised classification of potential asymmetric regions as the set of regions corresponding to brain injuries. Experimental results are carried out to demonstrate the efficacy of the approach.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132318944","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

Image matching in large scale indoor environment 大规模室内环境下的图像匹配

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204357

Hongwen Kang, Alexei A. Efros, M. Hebert, T. Kanade

引用次数: 57

A level set-based global shape prior and its application to image segmentation 基于水平集的全局形状先验及其在图像分割中的应用

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204275

Lei Zhang, Q. Ji

引用次数: 1

A coding scheme for indexing multimodal biometric databases 索引多模态生物特征数据库的编码方案

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204311

A. Gyaourova, A. Ross

{"title":"A coding scheme for indexing multimodal biometric databases","authors":"A. Gyaourova, A. Ross","doi":"10.1109/CVPRW.2009.5204311","DOIUrl":"https://doi.org/10.1109/CVPRW.2009.5204311","url":null,"abstract":"In biometric identification systems, the identity associated with the input data is determined by comparing it against every entry in the database. This exhaustive matching process increases the response time of the system and, potentially, the rate of erroneous identification. A method that narrows the list of potential identities will allow the input data to be matched against a smaller number of identities. We describe a method for indexing large-scale multimodal biometric databases based on the generation of an index code for each enrolled identity. In the proposed method, the input biometric data is first matched against a small set of reference images. The set of ensuing match scores is used as an index code. The index codes of multiple modalities are then integrated using three different fusion techniques in order to further improve the indexing performance. Experiments on a chimeric face and fingerprint bimodal database indicate a 76% reduction in the search space at 100% hit rate. These results suggest that indexing has the potential to substantially improve the response time of multimodal biometric systems without compromising the accuracy of identification.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123920830","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: 37

Global and local quality measures for NIR iris video 近红外虹膜视频的全球和本地质量措施

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204310

Jinyu Zuo, N. Schmid

引用次数: 31

Egocentric recognition of handled objects: Benchmark and analysis 被处理对象的自我中心识别:基准与分析

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204360

Xiaofeng Ren, Matthai Philipose

{"title":"Egocentric recognition of handled objects: Benchmark and analysis","authors":"Xiaofeng Ren, Matthai Philipose","doi":"10.1109/CVPRW.2009.5204360","DOIUrl":"https://doi.org/10.1109/CVPRW.2009.5204360","url":null,"abstract":"Recognizing objects being manipulated in hands can provide essential information about a person's activities and have far-reaching impacts on the application of vision in everyday life. The egocentric viewpoint from a wearable camera has unique advantages in recognizing handled objects, such as having a close view and seeing objects in their natural positions. We collect a comprehensive dataset and analyze the feasibilities and challenges of the egocentric recognition of handled objects. We use a lapel-worn camera and record uncompressed video streams as human subjects manipulate objects in daily activities. We use 42 day-to-day objects that vary in size, shape, color and textureness. 10 video sequences are shot for each object under different illuminations and backgrounds. We use this dataset and a SIFT-based recognition system to analyze and quantitatively characterize the main challenges in egocentric object recognition, such as motion blur and hand occlusion, along with its unique constraints, such as hand color, location prior and temporal consistency. SIFT-based recognition has an average recognition rate of 12%, and reaches 20% through enforcing temporal consistency. We use simulations to estimate the upper bound for SIFT-based recognition at 64%, the loss of accuracy due to background clutter at 20%, and that of hand occlusion at 13%. Our quantitative evaluations show that the egocentric recognition of handled objects is a challenging but feasible problem with many unique characteristics and many opportunities for future research.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122960861","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: 114

3D segmentation of rodent brains using deformable models and variational methods 利用变形模型和变分方法对啮齿动物大脑进行三维分割

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204051

Shaoting Zhang, Jinghao Zhou, Xiaoxu Wang, Sukmoon Chang, Dimitris N. Metaxas, George J. Pappas, F. Delis, N. Volkow, Gene-Jack Wang, P. Thanos, C. Kambhamettu

{"title":"3D segmentation of rodent brains using deformable models and variational methods","authors":"Shaoting Zhang, Jinghao Zhou, Xiaoxu Wang, Sukmoon Chang, Dimitris N. Metaxas, George J. Pappas, F. Delis, N. Volkow, Gene-Jack Wang, P. Thanos, C. Kambhamettu","doi":"10.1109/CVPRW.2009.5204051","DOIUrl":"https://doi.org/10.1109/CVPRW.2009.5204051","url":null,"abstract":"3D functional segmentation of brain images is important in understating the relationships between anatomy and mental diseases in brains. Volumetric analysis of various brain structures such as the cerebellum plays a critical role in studying the structural changes in brain regions as a function of development, trauma, or neurodegeneration. Although various segmentation methods in clinical studies have been proposed, many of them require a priori knowledge about the locations of the structures of interest, which prevents the fully automatic segmentation. Besides, the topological changes of structures are difficult to detect. In this paper, we present a novel method for detecting and locating the brain structures of interest that can be used for the fully automatic 3D functional segmentation of rodent brain MR images. The presented method is based on active shape model (ASM), Metamorph models and variational techniques. It focuses on detecting the topological changes of brain structures based on a novel volume ratio criteria. The mean successful rate of the topological change detection shows 86.6% accuracy compared to the expert identified ground truth.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126440900","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

Quasiconvex alignment of multimodal skin images for quantitative dermatology 定量皮肤科多模态皮肤图像的拟凸对齐

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/CVPRW.2009.5204346

S. Madan, Kristin J. Dana, G. O. Cula

{"title":"Quasiconvex alignment of multimodal skin images for quantitative dermatology","authors":"S. Madan, Kristin J. Dana, G. O. Cula","doi":"10.1109/CVPRW.2009.5204346","DOIUrl":"https://doi.org/10.1109/CVPRW.2009.5204346","url":null,"abstract":"In quantitative dermatology, high resolution sensors provide images that capture fine scale features like pores, birthmarks, and moles. Breathing and minute movements result in misregistration of micro level features. Many computer vision methods for dermatology such as change detection, appearance capture, and multi sensor fusion require high accuracy point-wise registration of micro level features. However, most computer vision algorithms are based on macro level features such as eyes, nose, and lips, and aren't suitable for registering micro level features. In this paper, we develop a practical robust algorithm to align face regions using skin texture with mostly indistinct micro level features. In computer vision, these regions would typically be considered featureless regions. Our method approximates the face surface as a collection of quasi-planar skin patches and uses quasiconvex optimization and the L∞ norm for estimation of spatially varying homographies. We have assembled a unique dataset of high resolution dermatology images comprised of over 100 human subjects. The image pairs vary in imaging modality (crossed, parallel and no polarization) and are misregistered due to the natural non-rigid human movement between image capture. This method of polarization based image capture is commonly used in dermatology to image surface and subsurface structure. Using this dataset, we show high quality alignment of “featureless” regions and demonstrate that the algorithm works robustly over a large set of subjects with different skin texture appearance, not just a few test images.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114686771","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 projector-camera system for creating a display with water drops 一种用水滴制作显示器的投影摄影机系统

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.1109/cvpr.2009.5204316

P. Barnum, S. Narasimhan, T. Kanade

{"title":"A projector-camera system for creating a display with water drops","authors":"P. Barnum, S. Narasimhan, T. Kanade","doi":"10.1109/cvpr.2009.5204316","DOIUrl":"https://doi.org/10.1109/cvpr.2009.5204316","url":null,"abstract":"Various non-traditional media, such as water drops, mist, and fire, have been used to create vibrant two and three dimensional displays. Usually such displays require a great deal of design and engineering. In this work, we show a computer vision based approach to easily calibrate and learn the properties of a three-dimensional water drop display, using a few pieces of off-the-shelf hardware. Our setup consists of a camera, projector, laser plane, and water drop generator. Based on the geometric calibration between the hardware, a user can “paint” the drops from the point of view of the camera, causing the projector to illuminate them with the correct color at the correct time. We first demonstrate an algorithm for the case where no drop occludes another from the point of view of either camera or projector. If there is no occlusion, the system can be trained once, and the projector plays a precomputed movie. We then show our work toward a display with real rain. In real time, our system tracks and predicts the future location of hundreds of drops per second, then projects rays to hit or miss each drop.","PeriodicalId":431981,"journal":{"name":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121864976","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

Efficient acquisition of human existence priors from motion trajectories 从运动轨迹中有效地获取人类存在先验

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Pub Date : 2009-06-20 DOI: 10.2197/ipsjtcva.2.145

H. Habe, Hidehito Nakagawa, M. Kidode

引用次数: 1