2010 Western New York Image Processing Workshop最新文献

Quality versus intelligibility: Studying human preferences for american sign language video 质量与可理解性:研究人类对美国手语视频的偏好

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1117/12.876733

Frank M. Ciaramello, S. Hemami

引用次数: 10

Determining camera pose using free-form lines 使用自由形式的线条确定相机姿势

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649747

S. Nagarajan, T. Schenk, B. Csathó

引用次数: 0

A HVS-driven image segmentation framework using a local segmentation performance measure 一个hvs驱动的图像分割框架，使用局部分割性能度量

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649767

Renbin Peng, P. Varshney

引用次数: 0

Development of a web-based blind test to score and rank hyperspectral classification algorithms 开发基于网络的盲测，对高光谱分类算法进行评分和排序

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649748

K. King, J. Kerekes

引用次数: 6

Tree-metrics graph cuts for brain MRI segmentation with tree cutting 树形图切割用于脑MRI分割

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649772

R. Fang, Yu-hsin Joyce Chen, R. Zabih, Tsuhan Chen

{"title":"Tree-metrics graph cuts for brain MRI segmentation with tree cutting","authors":"R. Fang, Yu-hsin Joyce Chen, R. Zabih, Tsuhan Chen","doi":"10.1109/WNYIPW.2010.5649772","DOIUrl":"https://doi.org/10.1109/WNYIPW.2010.5649772","url":null,"abstract":"We tackle the problem of brain MRI image segmentation using the tree-metric graph cuts (TM) algorithm, a novel image segmentation algorithm, and introduce a “tree-cutting” method to interpret the labeling returned by the TM algorithm as tissue classification for the input brain MRI image. The approach has three steps: 1) pre-processing, which generates a tree of labels as input to the TM algorithm; 2) a sweep of the TM algorithm, which returns a globally optimal labeling with respect to the tree of labels; 3) post-processing, which involves running the “tree-cutting” method to generate a mapping from labels to tissue classes (GM, WM, CSF), producing a meaningful brain MRI segmentation. The TM algorithm produces a globally optimal labeling on tree metrics in one sweep, unlike conventional methods such as EMS and EM-style geo-cuts, which iterate the expectation maximization algorithm to find hidden patterns and produce only locally optimal labelings. When used with the “tree-cutting” method, the TM algorithm produces brain MRI segmentations that are as good as the Unified Segmentation algorithm used by SPM8, using a much weaker prior. Comparison with the current approaches shows that our method is faster and that our overall segmentation accuracy is better.","PeriodicalId":210139,"journal":{"name":"2010 Western New York Image Processing Workshop","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133081408","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

Human-centric approaches to image understanding and retrieval 以人为中心的图像理解和检索方法

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649743

Rui Li, Preethi Vaidyanathan, Sai Mulpuru, J. Pelz, P. Shi, C. Calvelli, Anne R. Haake

{"title":"Human-centric approaches to image understanding and retrieval","authors":"Rui Li, Preethi Vaidyanathan, Sai Mulpuru, J. Pelz, P. Shi, C. Calvelli, Anne R. Haake","doi":"10.1109/WNYIPW.2010.5649743","DOIUrl":"https://doi.org/10.1109/WNYIPW.2010.5649743","url":null,"abstract":"The amount of digital medical image data is increasing rapidly in terms of both quantity and heterogeneity. There exists a great need to format medical image archives so as to facilitate diagnostics and preventive medicine. To achieve this, in the past few decades great efforts have been made to investigate methods of applying content-based image retrieval (CBIR) techniques to retrieve images. However, several critical challenges remain. Recently, CBIR research has become intertwined with the fundamental problem of image understanding and it is recognized that computing solutions that bridge the “semantic gap” must capture higher-level domain knowledge of medical end users. We are investigating the incorporation of state-of-the-art visual categorization techniques into conventional CBIR approaches. Visual attention deployment strategies of medical experts serve as an objective measure to help us understand the perceptual and conceptual processes involved in identifying key visual features and selecting diagnostic regions of the images. Understanding these processes will inform and direct feature selection approaches on medical images, such as the dermatological images used in our study. We also explore systematic and effective information integration methods of image data and semantic descriptions with the long-term goals of building efficient human-centered multi-modal interactive CBIR systems.","PeriodicalId":210139,"journal":{"name":"2010 Western New York Image Processing Workshop","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127747028","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

Boosting with stereo features for building facade detection on mobile platforms 增强立体特征，用于移动平台上的建筑立面检测

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649753

J. Delmerico, Jason J. Corso, P. David

引用次数: 7

Print engine color management using customer image content 打印引擎色彩管理使用客户图像内容

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649758

Michael W. Elliot, J. Cockburn

{"title":"Print engine color management using customer image content","authors":"Michael W. Elliot, J. Cockburn","doi":"10.1109/WNYIPW.2010.5649758","DOIUrl":"https://doi.org/10.1109/WNYIPW.2010.5649758","url":null,"abstract":"The production of quality color prints requires that color accuracy and reproducibility be maintained to within very tight tolerances when transferred to different media. Variations in the printing process commonly produce color shifts that result in poor color reproduction. The primary function of a color management system is maintaining color quality and consistency. Currently these systems are tuned in the factory by printing a large set of test color patches, measuring them, and making necessary adjustments. This time-consuming procedure should be repeated as needed once the printer leaves the factory. In this work, a color management system that compensates for print color shifts in realtime using feedback from an in-line full-width sensor is proposed. Instead of printing test patches, this novel attempt at color management utilizes the output pixels already rendered in production pages, for a continuous printer characterization. The printed pages are scanned in-line and the results are utilized to update the process by which colorimetric image content is translated into engine specific color separations (e.g. CIELAB->CMYK). The proposed system provides a means to perform automatic printer characterization, by simply printing a set of images that cover the gamut of the printer. Moreover, all of the color conversion features currently utilized in production systems (such as Gray Component Replacement, Gamut Mapping, and Color Smoothing) can be achieved with the proposed system.","PeriodicalId":210139,"journal":{"name":"2010 Western New York Image Processing Workshop","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125127626","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

Advanced situational awareness and obstacle detection using a monocular camera 使用单目摄像机的先进态势感知和障碍物检测

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649763

Abhijit Bhoite, N. Beke, Sashank Nanduri, Timothy Duffy, M. Torres

引用次数: 1

Hierarchical image clustering for analyzing eye tracking videos 用于眼动追踪视频分析的分层图像聚类

2010 Western New York Image Processing Workshop Pub Date : 2010-12-03 DOI: 10.1109/WNYIPW.2010.5649742

Thomas B. Kinsman, P. Bajorski, J. Pelz

引用次数: 5