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Titlebook: Human Ear Recognition by Computer; Bir Bhanu,Hui Chen Book 2008 Springer-Verlag London 2008 3D.Computer Vision.Ear Recognition.Ear-based i

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發(fā)表于 2025-3-21 17:01:35 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Human Ear Recognition by Computer
編輯Bir Bhanu,Hui Chen
視頻videohttp://file.papertrans.cn/430/429122/429122.mp4
概述Offers complete coverage of human ear recognition.Describes complete human recognition systems using 3D ear biometrics.Includes new biometrics, new application and results on the latest available data
叢書名稱Advances in Computer Vision and Pattern Recognition
圖書封面Titlebook: Human Ear Recognition by Computer; Bir Bhanu,Hui Chen Book 2008 Springer-Verlag London 2008 3D.Computer Vision.Ear Recognition.Ear-based i
描述.Biometrics deal with recognition of individuals based on their physiological or behavioural characteristics. Researchers have done extensive studies on biometrics such as fingerprint, face, palm print, iris and gait. Ear, a viable new class of biometrics, has certain advantages over face and fingerprint, which are the two most common biometrics in both academic research and industrial applications...This book explores all aspects of 3D ear recognition: representation, detection, recognition, indexing and performance prediction. It uses large datasets to quantify and compare the performance of various techniques...Features and topics include: Ear detection and recognition in 2D image - 3D object recognition and 3D biometrics - 3D ear recognition - Performance comparison and prediction...The techniques discussed will be of great interest to researchers, developers and decision makers who are involved in robust human recognition by computer for a large number of practical applications..
出版日期Book 2008
關(guān)鍵詞3D; Computer Vision; Ear Recognition; Ear-based identification; Human Recognition; Performance; Security; a
版次1
doihttps://doi.org/10.1007/978-1-84800-129-9
isbn_softcover978-1-84996-733-4
isbn_ebook978-1-84800-129-9Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightSpringer-Verlag London 2008
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Recognizing 3D Ears Using Ear Helix/Anti-Helix,) algorithm is run to improve the transformation which brings the gallery ear and probe ear into the best alignment, for every gallery-probe pair. The root mean square (RMS) registration error is used as the matching error criterion. The subject in the gallery with the minimum RMS error is declared as the recognized person in the probe image.
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Summary and FutureWork,With the decreasing cost (few thousand dollars) and size of a 3D scanner and the increased performance, we believe that 3D ear biometrics will be highly useful in many real-world applications in the future.
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發(fā)表于 2025-3-22 16:27:52 | 只看該作者
3D Ear Detection from Side Face Range Images,d detection, and fusion of color and range images and global-to-local registration based detection. The first two approaches only use range images, and the third approach fuses the color and range images.
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發(fā)表于 2025-3-22 18:37:14 | 只看該作者
Performance Prediction of a 3D Ear Recognition System,tch and non-match distances obtained from matching 3D ears are used to estimate their distributions. By modeling cumulative match characteristic (CMC) curve as a binomial distribution, the ear recognition performance can be predicted on a larger gallery.
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world‘s leading mobile platform, according to Gartner.Beginning Android 4 Games Development .offers everything you need to join the ranks of successful Android game developers. You‘ll start with game design fundamentals and programming basics, and then progress toward creating your own basic game en
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