32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings.最新文献_第2页

Tracking and handoff between multiple perspective camera views 跟踪和切换之间的多视角相机视图

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284284

S. Guler, John M. Griffith, Ian A. Pushee

引用次数: 20

Photo-realistic representation of anatomical structures for medical education by fusion of volumetric and surface image data 基于体积和表面图像数据融合的医学教育解剖结构的逼真表现

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284261

Arthur W. Wetzel, G. L. Nieder, Geri Durka-Pelok, T. Gest, S. Pomerantz, Démian Nave, S. Czanner, Lynn Wagner, Ethan Shirey, D. Deerfield

{"title":"Photo-realistic representation of anatomical structures for medical education by fusion of volumetric and surface image data","authors":"Arthur W. Wetzel, G. L. Nieder, Geri Durka-Pelok, T. Gest, S. Pomerantz, Démian Nave, S. Czanner, Lynn Wagner, Ethan Shirey, D. Deerfield","doi":"10.1109/AIPR.2003.1284261","DOIUrl":"https://doi.org/10.1109/AIPR.2003.1284261","url":null,"abstract":"We have produced improved photo-realistic views of anatomical structures for medical education combining data from photographic images of anatomical surfaces with optical, CT and MRI volumetric data such as provided by the NLM Visible Human Project. Volumetric data contains the information needed to construct 3D geometrical models of anatomical structures, but cannot provide a realistic appearance for surfaces. Nieder has captured high quality photographic sequences of anatomy specimens over a range of rotational angles. These have been assembled into QuickTime VR Object movies that can be viewed statically or dynamically. We reuse this surface imagery to produce textures and surface reflectance maps for 3D anatomy models to allow viewing from any orientation and lighting condition. Because the volumetric data comes from different individuals than the surface images, we have to warp these data into alignment. Currently we do not use structured lighting or other direct 3D surface information, so surface shape is recovered from rotational sequences using silhouettes and texture correlations. The results of this work improves the appearance and generality of models, used for anatomy instruction with the PSC Volume Browser.","PeriodicalId":176987,"journal":{"name":"32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127179649","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

Associative memory based on ratio learning for real time skin color detection 基于比例学习的联想记忆实时肤色检测

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284264

Ming-Jung Seow, V. Asari

{"title":"Associative memory based on ratio learning for real time skin color detection","authors":"Ming-Jung Seow, V. Asari","doi":"10.1109/AIPR.2003.1284264","DOIUrl":"https://doi.org/10.1109/AIPR.2003.1284264","url":null,"abstract":"A novel approach for skin color modeling using ratio rule learning algorithm is proposed in this paper. The learning algorithm is applied to a real time skin color detection application. The neural network learn, based on the degree of similarity between the relative magnitudes of the output of each neuron with respect to that of all other neurons. The activation/threshold function of the network is determined by the statistical characteristic of the input patterns. Theoretical analysis has shown that the network is able to learn and recall the trained patterns without much problem. It is shown mathematically that the network system is stable and converges in all circumstances for the trained patterns. The network utilizes the ratio-learning algorithm for modeling the characteristic of skin color in the RGB space as a linear attractor. The skin color will converge to a line of attraction. The new technique is applied to images captured by a surveillance camera and it is observed that the skin color model is capable of processing 420/spl times/315 resolution images of 24-bit color at 30 frames per second in a dual Xeon 2.2 GHz CPU workstation running Windows 2000.","PeriodicalId":176987,"journal":{"name":"32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130708380","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

Imaging of moving targets using a Doppler compensated multiresolution method 运动目标的多普勒补偿多分辨率成像方法

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284251

R. Bonneau

引用次数: 6

Image formation through walls using a distributed radar sensor array 利用分布式雷达传感器阵列通过墙壁形成图像

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284277

A. Hunt

引用次数: 44

Eigenviews for object recognition in multispectral imaging systems 多光谱成像系统中目标识别的特征图

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284245

R. Ramanath, W. Snyder, H. Qi

{"title":"Eigenviews for object recognition in multispectral imaging systems","authors":"R. Ramanath, W. Snyder, H. Qi","doi":"10.1109/AIPR.2003.1284245","DOIUrl":"https://doi.org/10.1109/AIPR.2003.1284245","url":null,"abstract":"We address the problem of representing multispectral images of objects using eigenviews for recognition purposes. Eigenviews have long been used for object recognition and pose estimation purposes in the grayscale and color image settings. The purpose of this paper is two-fold: firstly to extend the idealogies of eigenviews to multispectral images and secondly to propose the use of dimensionality reduction techniques other than those popularly used. Principal Component Analysis (PCA) and its various kernel-based flavors are popularly used to extract eigenviews. We propose the use of Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) as possible candidates for eigenview extraction. Multispectral images of a collection of 3D objects captured under different viewpoint locations are used to obtain representative views (eigenviews) that encode the information in these images. The idea is illustrated with a collection of eight synthetic objects imaged in both reflection and emission bands. A Nearest Neighbor classifier is used to perform the classification of an arbitrary view of an object. Classifier performance under additive white Gaussian noise is also tested. The results demonstrate that this system holds promise for use in object recognition under the multispectral imaging setting and also for novel dimensionality reduction techniques. The number of eigenviews needed by various techniques to obtain a given classifier accuracy is also calculated as a measure of the performance of the dimensionality reduction technique.","PeriodicalId":176987,"journal":{"name":"32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings.","volume":"18 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116091850","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: 26

A survey of recent developments in theoretical neuroscience and machine vision 理论神经科学和机器视觉的最新发展综述

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284273

J. Colombe

引用次数: 2

A real-time wide field of view passive millimeter-wave imaging camera 实时宽视场无源毫米波成像相机

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284280

S. Clark, C. Martin, Peter J. Costianes, V. Kolinko, J. Lovberg

引用次数: 14

Stereo mosaics with slanting parallel projections from many cameras or a moving camera 立体马赛克与倾斜平行投影从许多相机或移动相机

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284282

Zhigang Zhu

引用次数: 6

Visual literacy: an overview 视觉素养:概述

32nd Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. Pub Date : 2003-10-15 DOI: 10.1109/AIPR.2003.1284270

J. Aanstoos

引用次数: 19