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Automated face tracking and recognitionHesher, Matthew Curtis. Erlebacher, Gordon. January 2003 (has links)
Thesis (M.S.)--Florida State University, 2003. / Advisor: Dr. Gordon Erlebacher, Florida State University, College of Arts and Sciences, Dept. of Computer Science. Title and description from dissertation home page (viewed Apr. 06, 2004). Includes bibliographical references.
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Infrared face recognition /Lee, Colin K. January 2004 (has links) (PDF)
Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Monique P. Fargues, Gamani Karunasiri. Includes bibliographical references (p. 135-136). Also available online.
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Face Recognition using Local Descriptors and Different Classification SchemasLiu,Ting Unknown Date
No description available.
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Illumination-robust face recognitionBatur, Aziz Umit 08 1900 (has links)
No description available.
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Three-dimensional morphanalysis of the faceTiddeman, Bernard January 1998 (has links)
No description available.
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Aspects of facial biometrics for verification of personal identityRamos Sanchez, M. Ulises January 2000 (has links)
No description available.
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Remote surveillance and face tracking with mobile phones (smart eyes).Da Silva, Sandro Cahanda Marinho January 2005 (has links)
This thesis addresses analysis, evaluation and simulation of low complexity face detection algorithms and tracking that could be used on mobile phones. Network access control using face recognition increases the user-friendliness in human-computer interaction. In order to realize a real time system implemented on handheld devices with low computing power, low complexity algorithms for face detection and face tracking are implemented. Skin color detection algorithms and face matching have low implementation complexity suitable for authentication of cellular network services. Novel approaches for reducing the complexities of these algorithms and fast implementation are introduced in this thesis. This includes a fast algorithm for face detection in video sequences, using a skin color model in the HSV (Hue-Saturation-Value) color space. It is combined with a Gaussian model of the H and S statistics and adaptive thresholds. These algorithms permit segmentation and detection of multiple faces in thumbnail images. Furthermore we evaluate and compare our results with those of a method implemented in the Chromatic Color space (YCbCr). We also test our test data on face detection method using Convolutional Neural Network architecture to study the suitability of using other approaches besides skin color as the basic feature for face detection. Finally, face tracking is done in 2D color video streams using HSV as the histogram color space. The program is used to compute 3D trajectories for a remote surveillance system.
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Performance evaluation of face recognition using frames of ten pose angles /El Seuofi, Sherif M. January 2007 (has links)
Thesis (M.S.)--Youngstown State University, 2007. / Includes bibliographical references (leaves 24-28).
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Representations and matching techniques for 3D free-form object and face recognition /Mian, Ajmal Saeed. January 2006 (has links)
Thesis (Ph.D.)--University of Western Australia, 2007.
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Mitigating the effect of covariates in face recognitionSingh, Richa, January 2008 (has links)
Thesis (Ph. D.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains xv, 136 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 125-136).
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