2008 IEEE Workshop on Applications of Computer Vision最新文献_第3页

Color Photometric Stereo for Albedo and Shape Reconstruction 用于反照率和形状重建的彩色光度立体

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544015

O. Ikeda, Y. Duan

引用次数: 17

Distributed Visual Processing for a Home Visual Sensor Network 基于分布式视觉处理的家庭视觉传感器网络

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544043

Kwangsu Kim, G. Medioni

引用次数: 7

Localization and Segmentation of A 2D High Capacity Color Barcode 二维大容量彩色条码的定位与分割

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544033

Devi Parikh, Gavin Jancke

引用次数: 143

Recovering Social Networks From Massive Track Datasets 从大量轨道数据集中恢复社交网络

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544042

C. Connolly, J. Burns, H. Bui

引用次数: 13

Explanation-Based Object Recognition 基于解释的物体识别

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544019

Geoffrey Levine, G. DeJong

{"title":"Explanation-Based Object Recognition","authors":"Geoffrey Levine, G. DeJong","doi":"10.1109/WACV.2008.4544019","DOIUrl":"https://doi.org/10.1109/WACV.2008.4544019","url":null,"abstract":"Many of today's visual scene and object categorization systems learn to classify using a statistical profile over a large number of small-scale local features sampled from the image. While some application systems have been constructed, this technology has enjoyed far more success in the research setting. The approach is best suited to tasks where within-class variability is small compared to between-class variability. This condition holds for large diverse artificial collections such as CalTech 101 where most categories have little to do with each other, but it often does not hold among naturalistic application-driven categories. Here, category distinctions are more likely to be conceptual or functional, and within-class differences can rival or exceed between- class differences. In this paper, we show how the local feature approach can be extended using explanation-based learning (EBL). The EBL approach makes use of readily available prior domain knowledge assembled into plausible explanations for why a training example's observable features might merit its assigned training label. Explanations expose additional semantic features and suggest how those hidden features may be estimated from observable features. We exhibit our approach on two CalTech 101 dataset tasks that we argue are emblematic of applied domains: Ketch vs. Schooner and Airplane vs. Background. In both cases classification accuracy is significantly improved.","PeriodicalId":439571,"journal":{"name":"2008 IEEE Workshop on Applications of Computer Vision","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132331339","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

Cata-Fisheye Camera for Panoramic Imaging 用于全景成像的鱼眼相机

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544035

Gurunandan Krishnan, S. Nayar

{"title":"Cata-Fisheye Camera for Panoramic Imaging","authors":"Gurunandan Krishnan, S. Nayar","doi":"10.1109/WACV.2008.4544035","DOIUrl":"https://doi.org/10.1109/WACV.2008.4544035","url":null,"abstract":"We present a novel panoramic imaging system which uses a curved mirror as a simple optical attachment to a fish- eye lens. When compared to existing panoramic cameras, our \"'cata-fisheye\" camera has a simple, compact and inexpensive design, and yet yields high optical performance. It captures the desired panoramic field of view in two parts. The upper part is obtained directly by the fisheye lens and the lower part after reflection by the curved mirror. These two parts of the field of view have a small overlap that is used to stitch them into a single seamless panorama. The cata-fisheye concept allows us to design cameras with a wide range of fields of view by simply varying the parameters and position of the curved mirror. We provide an automatic method for the one-time calibration needed to stitch the two parts of the panoramic field of view. We have done a complete performance evaluation of our concept with respect to (i) the optical quality of the captured images, (ii) the working range of the camera over which the parallax is negligible, and (iii) the spatial resolution of the computed panorama. Finally, we have built a prototype cata-fisheye video camera with a spherical mirror that can capture high resolution panoramic images (3600times550pixels) with a 360deg (horizontal) x 55deg (vertical) field of view.","PeriodicalId":439571,"journal":{"name":"2008 IEEE Workshop on Applications of Computer Vision","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132480322","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

Recognition of Human Actions using an Optimal Control Based Motor Model 基于最优控制的运动模型的人类行为识别

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544021

Sumitra Ganesh, R. Bajcsy

引用次数: 5

Locally Adjusted Robust Regression for Human Age Estimation 人类年龄估计的局部校正稳健回归

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544009

G. Guo, Yun Fu, Thomas S. Huang, C. Dyer

引用次数: 133

Qualitative Assessment of Video Stabilization and Mosaicking Systems 视频防抖和拼接系统的定性评价

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544008

Chao Zhang, P. Chockalingam, Ankit Kumar, P. Burt, Arvind Lakshmikumar

{"title":"Qualitative Assessment of Video Stabilization and Mosaicking Systems","authors":"Chao Zhang, P. Chockalingam, Ankit Kumar, P. Burt, Arvind Lakshmikumar","doi":"10.1109/WACV.2008.4544008","DOIUrl":"https://doi.org/10.1109/WACV.2008.4544008","url":null,"abstract":"Image stabilization is a key preprocessing step in dynamic image analysis, which deals with the removal of unwanted motion in a video sequence. It is principally understood as the warping of video sequences resulting in a total or partial removal of image motion. Stabilization is invaluable for motion analysis, structure from motion, independent motion detection, geo-registration and mosaicking, autonomous vehicle navigation, model-based compression, and many others. Given the usefulness of image stabilization for many applications, a variety of algorithms have been proposed to perform this task, and many real-time systems have been built to stabilize the real-time videos and provide motion data for tracking and geo-registrations. However, even though there are on-line libraries that provide test videos, there has been no established methods or industrial standards based on which the performance of a stabilization algorithm or system can be measured. This paper aims to address this gap and suggests an evaluation methodology which would provide us the ability to qualitatively measure the performance of a given stabilized system. We propose a performance measurement system and define the performance metrics in this paper. We then apply the assessment to two typical stabilization systems. The discussed methods can be used to benchmark video stabilization systems.","PeriodicalId":439571,"journal":{"name":"2008 IEEE Workshop on Applications of Computer Vision","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130766368","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

Online/Realtime Structure and Motion for General Camera Models 一般相机模型的在线/实时结构和运动

2008 IEEE Workshop on Applications of Computer Vision Pub Date : 2008-01-07 DOI: 10.1109/WACV.2008.4544016

G. Schweighofer, Sinisa Segvic, A. Pinz

引用次数: 21