Proceedings Fifth IEEE Workshop on Applications of Computer Vision最新文献

Automatic description of complex buildings with multiple images 复杂建筑物的多幅图像自动描述

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895417

Z. Kim, A. Huertas, R. Nevatia

引用次数: 113

Urban street grid description and verification 城市街道网格描述与验证

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895416

K. Price

引用次数: 32

Automatic image segmentation and classification using on-line shape learning 基于在线形状学习的自动图像分割和分类

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895404

Kyoung-Mi Lee, W. Street

引用次数: 13

Achieving accurate colour image segmentation in 2D and 3D with LVQ classifiers and partial adaptable class-specific representation 利用LVQ分类器和部分可适应的类别特定表示实现二维和三维彩色图像的精确分割

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895405

C. F. Nielsen, P. Passmore

{"title":"Achieving accurate colour image segmentation in 2D and 3D with LVQ classifiers and partial adaptable class-specific representation","authors":"C. F. Nielsen, P. Passmore","doi":"10.1109/WACV.2000.895405","DOIUrl":"https://doi.org/10.1109/WACV.2000.895405","url":null,"abstract":"Adaptable Class-Specific Representation (ACSR) has previously been used as a solution to the problem of segmentation near edges in 2D colour images. Sampling windows of fixed shape used in many segmentation approaches cause misrepresentation of texture classes. ACSR greatly reduces this problem, based on simple templates, resulting in accurate semi-automatic segmentation. The price of accuracy in ACSR is high processing overhead. We introduce an initial segmentation step using a faster fixed-shape window sampling and Learning Vector Quantization, and apply ACSR only at edge point. Processing speed is significantly increased without compromising segmentation accuracy. ACSR segmentation is particularly interesting for medical applications where correct shape and size is important. We extend the ACSR framework to true 3D volume segmentation. 3D information is used for classification at all sampling points, producing better results than per slice pseudo-3D segmentation. Colour volumes based on the Visible Human Project are used to demonstrate the approach. We conclude that ACSR can produce accurate segmentation in colour 2D images and 3D volumes, and that partial ACSR can significantly reduce processing overhead without losing segmentation quality.","PeriodicalId":306720,"journal":{"name":"Proceedings Fifth IEEE Workshop on Applications of Computer Vision","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126503107","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

Image sequence analysis for real-time underwater cable tracking 用于水下电缆实时跟踪的图像序列分析

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895427

A. Ortiz, M. Simo, G. Oliver

引用次数: 12

Tracking and pose estimation for computer assisted localization in industrial environments 工业环境中计算机辅助定位的跟踪和姿态估计

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895425

Xiang Zhang, Nassir Navab

{"title":"Tracking and pose estimation for computer assisted localization in industrial environments","authors":"Xiang Zhang, Nassir Navab","doi":"10.1109/WACV.2000.895425","DOIUrl":"https://doi.org/10.1109/WACV.2000.895425","url":null,"abstract":"One of the common needs for many real-time augmented reality (AR) applications is the precise 'localization'. Currently at Siemens Corporate Research (SCR), we are developing a real-time system for industrial maintenance assistance. The user is moving within a large industrial site. In order to provide the user with additional information the system needs to locate the user in both real and virtual world. In this scenario, the user is equipped with a mobile computer. The objective is to track and locate the user using a camera attached to the mobile computer. With a set of coded visual markers pre-registered with the global coordinate system, the optical localization could be solved by marker detection, tracking and pose estimation. In this paper, we present the real-time marker detection and pose estimation algorithms used in our mobile localization application. To work in large and complicated industrial environments, our system needs to recover localization information from limited correspondences. We consider two different pose estimation algorithms: the homography based algorithm and the 3-point algorithm. In this paper, we present the results of the numerical experiments comparing these two methods. The experiments are carried out to determine the best approach for our application and to evaluate the accuracy and limitations of the algorithms.","PeriodicalId":306720,"journal":{"name":"Proceedings Fifth IEEE Workshop on Applications of Computer Vision","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131823426","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: 29

Restoration of multiple images with motion blur in different directions 具有不同方向运动模糊的多幅图像的恢复

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895398

A. Rav-Acha, Shmuel Peleg

引用次数: 75

Learning partitioned least squares filters for fingerprint enhancement 学习指纹增强的分割最小二乘滤波器

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895395

S. Ghosal, Raghavendra Udupa, Sharath Pankanti, N. Ratha

引用次数: 6

Global matching criterion and color segmentation based stereo 基于立体的全局匹配准则和颜色分割

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895429

Hai Tao, H. Sawhney

引用次数: 117

Flame recognition in video 视频中的火焰识别

Proceedings Fifth IEEE Workshop on Applications of Computer Vision Pub Date : 2000-12-04 DOI: 10.1109/WACV.2000.895426

Walter Phillips, M. Shah, N. Lobo

{"title":"Flame recognition in video","authors":"Walter Phillips, M. Shah, N. Lobo","doi":"10.1109/WACV.2000.895426","DOIUrl":"https://doi.org/10.1109/WACV.2000.895426","url":null,"abstract":"This paper presents an automatic system for fire detection in video sequences. There are many previous methods to detect fire, however, all except two use spectroscopy or particle sensors. The two that use visual information suffer from the inability to cope with a moving camera or a moving scene. One of these is not able to work on general data, such as movie sequences. The other is too simplistic and unrestrictive in determining what is considered fire, so that it can be used reliably only in aircraft dry bays. Our system uses color and motion information computed from video sequences to locate fire. This is done by first using an approach that is based upon creating a Gaussian-smoothed color histogram to determine the fire-colored pixels, and then using the temporal variation of pixels to determine which of these pixels are actually fire. Unlike the two previous vision-based methods for pre detection, our method is applicable to more areas because of its insensitivity to camera motion. Two specific applications not possible with previous algorithms are the recognition of fire in the presence of global camera motion or scene motion and the recognition of fire in movies for possible use in an automatic rating system. We show that our method works in a variety of conditions, and that it can automatically determine when it has insufficient information.","PeriodicalId":306720,"journal":{"name":"Proceedings Fifth IEEE Workshop on Applications of Computer Vision","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125697352","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: 369