Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops最新文献_第8页

Driver State Monitor from DELPHI 来自DELPHI的驾驶员状态监视器

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.135

N. Edenborough, R. Hammoud, Andrew P. Harbach, A. Ingold, B. Kisačanin, P. Malawey, T. J. Newman, Gregory K. Scharenbroch, Steven G. Skiver, Mathew R Smith, Andrew Wilhelm, Gerard J Witt, E. Yoder, Harry Zhang

引用次数: 30

Camera Matchmoving in Unprepared, Unknown Environments 摄像机匹配移动在没有准备的，未知的环境

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.96

Manolis I. A. Lourakis, Antonis A. Argyros

引用次数: 6

RGB-Z: Mapping a Sparse Depth Map to a High Resolution RGB Camera Image RGB- z:将稀疏深度映射到高分辨率RGB相机图像

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.303

A. Rafii, C. Rossbach, Peter Zhao

引用次数: 0

Automatic Thermal Monitoring System (ATHEMOS) for Deception Detection 用于欺骗探测的自动热监测系统(ATHEMOS)

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.82

P. Buddharaju, J. Dowdall, P. Tsiamyrtzis, D. Shastri, Ioannis T. Pavlidis, M. Frank

{"title":"Automatic Thermal Monitoring System (ATHEMOS) for Deception Detection","authors":"P. Buddharaju, J. Dowdall, P. Tsiamyrtzis, D. Shastri, Ioannis T. Pavlidis, M. Frank","doi":"10.1109/CVPR.2005.82","DOIUrl":"https://doi.org/10.1109/CVPR.2005.82","url":null,"abstract":"Previous work has demonstrated the correlation of periorbital perfusion and stress levels in human beings. In this paper, we report results on a large and realistic mock-crime interrogation experiment. The interrogation is free flowing and no restrictions have been placed on the subjects. We propose a new methodology to compute the average periorbital temperature signal. The present approach addresses the deficiencies of the earlier methodology and is capable of coping with the challenges posed by the realistic setting. Specifically, it features a tandem condensation tracker to register the periorbital area in the context of a moving face. It operates on the raw temperature signal and tries to improve the information content by suppressing the noise level instead of amplifying the signal as a whole. Finally, a pattern recognition method classifies stressful (deceptive) from non-stressful (non-deceptive) subjects based on a comparative measure between the interrogation signal (baseline) and portions thereof (transient response).","PeriodicalId":89346,"journal":{"name":"Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops","volume":"10 1","pages":"1179"},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85384626","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 Flow-Based Approach to Vehicle Detection and Background Mosaicking in Airborne Video 基于流的机载视频车辆检测与背景拼接方法

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.29

H. Yalcin, M. Hebert, R. Collins, Michael J. Black

引用次数: 72

Face Modeling and Analysis in Stony Brook University 石溪大学人脸建模与分析

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.149

D. Samaras, Yang Wang, Lei Zhang, Sen Wang, Mohit Gupta

{"title":"Face Modeling and Analysis in Stony Brook University","authors":"D. Samaras, Yang Wang, Lei Zhang, Sen Wang, Mohit Gupta","doi":"10.1109/CVPR.2005.149","DOIUrl":"https://doi.org/10.1109/CVPR.2005.149","url":null,"abstract":"In this paper, we present our latest work on facial expression analysis, synthesis and face recognition. The advent of new technologies that allow the capture of massive amounts of high resolution, high frame rate face data, leads us to propose data-driven face models that accurately describe the appearance of faces under unknown pose and illumination conditions as well as to track subtle geometry changes that occur during expressions. In this paper, we also demonstrate our results for expression transfer among different subjects. We reduce the dimensionality of our data onto a lower dimensional space manifold and then decompose it into style and content parameters. This allows us to transfer subtle expression information (in the form of a style vector) between individuals to synthesize new expressions, as well as smoothly morph geometry and motion. Finally, we demonstrate the accuracy of our face modeling methods through an integrated example of image-driven re-targeting and relighting of facial expressions, where transfer of expression and illumination information between different individuals is possible.","PeriodicalId":89346,"journal":{"name":"Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops","volume":"1 1","pages":"1200"},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89535685","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: 1

8D-THERMO CAM: Combination of Geometry with Physiological Information for Face Recognition 8D-THERMO CAM:几何与生理信息相结合的人脸识别

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.13

I. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, Ioannis Konstantinidis, Mohammed N. Murtuza

{"title":"8D-THERMO CAM: Combination of Geometry with Physiological Information for Face Recognition","authors":"I. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, Ioannis Konstantinidis, Mohammed N. Murtuza","doi":"10.1109/CVPR.2005.13","DOIUrl":"https://doi.org/10.1109/CVPR.2005.13","url":null,"abstract":"Biometrics-based technologies in the area of identity management are gaining increasing importance, as a means of establishing non-falsifiable credentials for end users. However, in the three-way tug-of-war between convenient, unobtrusive data collection (required for user acceptance), accuracy in results (required for justifying deployment), and speed (required for widespread use in practice), no single biometric to date has managed to hold the middle ground that would allow for its ready adoption. The overall goal of our project is to develop the theoretical framework and computational tools that will lead to the development of a practical, unobtrusive, and accurate face recognition system for convenient and effective access control. This framework encompasses 8D characteristics of the face (3D geometry+2D visible texture+2D infrared texture, over time). In this paper, we present a novel multi-modal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. From the fitted parametric model we extract two images corresponding to the subject's face and process these images to extract biometric signatures. Specifically, the deformation image is compressed using a wavelet transform and the vasculature graph is extracted from the parametric thermal image.","PeriodicalId":89346,"journal":{"name":"Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops","volume":"70 1","pages":"1183"},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76452958","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

Interactive Montages of Sprites for Indexing and Summarizing Security Video 用于索引和总结安全视频的精灵的交互式蒙太奇

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.192

C. Pal, N. Jojic

{"title":"Interactive Montages of Sprites for Indexing and Summarizing Security Video","authors":"C. Pal, N. Jojic","doi":"10.1109/CVPR.2005.192","DOIUrl":"https://doi.org/10.1109/CVPR.2005.192","url":null,"abstract":"In this video we present a new model of interaction for indexing and visualizing video in the context of security applications. We present a method of indexing video by arranging irregularly shaped icons or sprites into a montage representing motion events or security events within the original video scene. The sprites in the montage are used as an index into the original video. We also generate video montages to summarize video in which motion events are compressed and overlayed in a video of shorter time duration. This summary video also acts as an index into the original video stream. We use a simple, novel method of extracting sprites for the image and video montages based on incrementally building a Gaussian mixture model with conjugate priors for the background. We then use fast morphological operators to extract foreground elements. Our approach can be viewed as a fast maximum a posteriori (MAP) inference procedure in a layered image model. The contributions of this work are new interaction and summary schemes that allow viewers to potentially survey hours of security video in the order of minutes.","PeriodicalId":89346,"journal":{"name":"Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops","volume":"13 1","pages":"1192"},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82345906","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: 27

Hand Tracking with Flocks of Features 具有特征群的手跟踪

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.173

M. Kölsch, M. Turk

{"title":"Hand Tracking with Flocks of Features","authors":"M. Kölsch, M. Turk","doi":"10.1109/CVPR.2005.173","DOIUrl":"https://doi.org/10.1109/CVPR.2005.173","url":null,"abstract":"Tracking hands in live video is a challenging task: the hand appearance can change too rapidly for appearance-based trackers to work, and color-based trackers (that do not rely on geometry) have to make limiting assumptions about the background color. This article shows the results of hand tracking with \"Flocks of Features\", a tracking method that combines motion cues and a learned foreground color distribution to achieve fast and robust 2D tracking of highly articulated objects. Many independent image artifacts are tracked from one frame to the next, adhering only to local constraints. This concept is borrowed from nature since these tracks mimic the flight of flocking birds - exhibiting local individualism and variability while maintaining a clustered entirety. Hand tracking has important applications for interaction with wearable computers, for intuitive manipulation of virtual objects, for detection of activity signatures, and much more. Tracking with Flocks of Features is not limited to hands - any articulated or appearance-changing object can benefit from this multi-cue tracking method.","PeriodicalId":89346,"journal":{"name":"Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops","volume":"23 1","pages":"1187"},"PeriodicalIF":0.0,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87528359","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: 53

Tracking People and Recognizing Their Activities 跟踪人员并识别他们的活动

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops Pub Date : 2005-06-20 DOI: 10.1109/CVPR.2005.353

Deva Ramanan, D. Forsyth, Andrew Zisserman

引用次数: 20