Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640)最新文献

The imaging issue in an automatic face/disguise detection system 人脸/伪装自动检测系统中的成像问题

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855246

I. Pavlidis, P. Symosek

{"title":"The imaging issue in an automatic face/disguise detection system","authors":"I. Pavlidis, P. Symosek","doi":"10.1109/CVBVS.2000.855246","DOIUrl":"https://doi.org/10.1109/CVBVS.2000.855246","url":null,"abstract":"Automatic face recognition systems have made great strides. They still, however cannot cope with changes due to lighting and cannot detect disguises, Both of these issues are critical for the employment of face recognition systems in high security applications, such as embassy perimeters, federal plazas, mid the like. We propose novel imaging solutions that address these difficult problems. We demonstrate with theoretical and experimental arguments that a dual-band fusion system in the near infrared can segment human faces much more accurately than traditional visible band face detection systems. Face detection is useful by itself as an early warning method in certain surveillance applications. Accurate face delineation can also improve the performance of face recognition systems in certain difficult scenarios, particularly in outside environments. We also demonstrate with theoretical and experimental arguments that the upper band of the near infrared (1.4-2.4 /spl mu/m) is particularly advantageous for disguise detection purposes. This is attributable to the unique and universal properties of the human skin in this sub-band. We conclude the paper with a description of our ongoing and future efforts.","PeriodicalId":231063,"journal":{"name":"Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125961849","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: 161

On cancer recognition of ultrasound images 肿瘤超声图像识别研究

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855257

E. Yfantis, T. Lazarakis, A. Popovich, A. Angelopoulos, G. Bebis

引用次数: 3

Thermal imaging for anxiety detection 热成像检测焦虑

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855255

I. Pavlidis, J. Levine, P. Baukol

引用次数: 141

Complexity analysis of ATR algorithms based on invariants 基于不变量的ATR算法复杂度分析

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855247

D. G. Arnold, K. Sturtz

引用次数: 5

History, current status, and future of infrared identification 红外识别技术的历史、现状与未来

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855245

F. Prokoski

引用次数: 162

3-D terrain from synthetic aperture radar images 合成孔径雷达图像的三维地形

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855251

A. Bors, E. Hancock, Richard C. Wilson

引用次数: 4

Recognition of occluded targets using stochastic models 基于随机模型的遮挡目标识别

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855252

B. Bhanu, Yingqiang Lin

引用次数: 2

Region of interest identification, feature extraction, and information fusion in a forward looking infrared sensor used in landmine detection 用于地雷探测的前视红外感兴趣区域识别、特征提取和信息融合

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855254

B. Nelson

{"title":"Region of interest identification, feature extraction, and information fusion in a forward looking infrared sensor used in landmine detection","authors":"B. Nelson","doi":"10.1109/CVBVS.2000.855254","DOIUrl":"https://doi.org/10.1109/CVBVS.2000.855254","url":null,"abstract":"A forward looking infrared sensor used in conjunction with a vehicular based landmine detection system is described. The paper first describes the requirements for vehicularly-deployed forward-looking infrared sensors. This is followed by descriptions of the basic forward looking infrared sensor, its components and its integration to the vehicular platform. This is followed by a description of a novel method that is used to define regions of interest within the infrared images in real time. Next the specific features that are extracted from the infrared images that are used in target classification are provided. The paper then describes a fuzzy inference system that evaluates the extracted data features and generates a mine confidence value that is used for final declaration of potential targets as mines or clutter. Specific examples of attained performance both with and without the fuzzy inference system are provided to demonstrate the efficacy of the fuzzy inference system in evaluating data features and performing the classification. Lastly, the paper describes other areas where the described methods are being successfully applied.","PeriodicalId":231063,"journal":{"name":"Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128570003","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: 6

Multi-resolution mesh based 3D object recognition 基于多分辨率网格的三维目标识别

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855248

Qing Li, Manli Zhou, Jian Liu

{"title":"Multi-resolution mesh based 3D object recognition","authors":"Qing Li, Manli Zhou, Jian Liu","doi":"10.1109/CVBVS.2000.855248","DOIUrl":"https://doi.org/10.1109/CVBVS.2000.855248","url":null,"abstract":"Motivated by the need of the numerous real-world applications, 3D object recognition has become an active research field. The representation describes the sensed data and the object models, and it is a key issue in the recognition process, which decides the match strategy and the effectiveness and robustness of the recognition system. In this paper, we propose an improved 3D object representation first, which computes the local signatures of a given basis polygon on the surface mesh, and converts the signatures to a 2D array called the distance-angle (DA) images by weighted bilinear interpolation. This representation is adaptive to free-form objects and resistant to occlusion and clutter. Compared with the original representation, it has a more distinct meaning, easier operation, and adaptation to different resolutions and irregular triangle meshes. Secondly, based on the improved representation, a novel 3D recognition algorithm is presented, which has multiresolution mesh based, coarse-to-fine recognition. By matching the DA image of a polygon in the scene surface mesh with the DA images of models at low resolution, a model candidate set is obtained. The set is filtered in the neighborhood of the matched polygons in a high-resolution mesh and verified by the model candidate sets of other polygons. Experiments show that this algorithm needs less computation and is very accurate and robust.","PeriodicalId":231063,"journal":{"name":"Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640)","volume":"15 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127645530","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

Simultaneous estimation of optical flow and heat transport in infrared image sequences 红外图像序列中光流和热输运的同时估计

Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (Cat. No.PR00640) Pub Date : 2000-06-13 DOI: 10.1109/CVBVS.2000.855253

H. Haussecker

引用次数: 11