This book presents a collection of high-quality research by leading experts in computer vision and its applications. Each of the 16 chapters can be read independently and discusses the principles of a specific topic, reviews up-to-date techniques, presents outcomes, and highlights the challenges and future directions. As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation. It is intended for postgraduate students, researchers, scholars and developers who are interested in computer vision and connected research disciplines, and is also suitable for senior undergraduate students who are taking advanced courses in related topics. However, it is also provides a valuable reference resource for practitioners from industry who want to keep abreast of recent developments in this dynamic, exciting and profitable research field.
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As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation.
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Computer Vision for Supporting Fashion Creative Processes.- Facial Features Detection and Localization.- Advances and Trends in Video Face Alignment.- Video Similarity Measurement and Search.- Analysis and Evaluation of Keypoint Descriptors for Image Matching.- Feature Extraction of Color images using Quaternion Moments.- Face recognition Using Exact Gaussian-Hermit Moments and Nonnegative Matrix Factorization.- Face Recognition with Discrete Orthogonal Moments.- Content-Based Image Retrieval using Multiresolution Feature Descriptors.- Landmark Recognition: From Small-Scale to Large-Scale Retrieval.- Ocean Ecosystems Plankton Classification.- Boundary Detection of Echocardiographic Images during Mitral Regurgitation.- Motion Estimation Made Easy: Evolution and Trends in Visual Odometry.- Deep Ear Recognition Pipeline.- Scene Classification Using Transfer Learning.- Hyperspectral Image: Fundamentals and Advances.
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This book presents a collection of high-quality research by leading experts in computer vision and its applications. Each of the 16 chapters can be read independently and discusses the principles of a specific topic, reviews up-to-date techniques, presents outcomes, and highlights the challenges and future directions. As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation. It is intended for postgraduate students, researchers, scholars and developers who are interested in computer vision and connected research disciplines, and is also suitable for senior undergraduate students who are taking advanced courses in related topics. However, it is also provides a valuable reference resource for practitioners from industry who want to keep abreast of recent developments in this dynamic, exciting and profitable research field.
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Offers a comprehensive overview of the most advanced theories, methodologies, and modern applications in computer vision Presents several new methods and robust algorithms, such as deep learning algorithms Covers topics such as object detection and recognition, human actions recognition, face detection and recognition, object segmentation, and shape models
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Produktdetaljer

ISBN
9783030029999
Publisert
2019-01-31
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Biographical note

Mahmoud Hassaballah was born in 1974 in Qena, Egypt. He received a B.Sc. degree in Mathematics in 1997, and an M.Sc. degree in Computer Science in 2003, both from South Valley University, Egypt. In April 2008, he joined the Lab of Intelligence Communication at the Department of Electrical and Electronic Engineering and Computer Science, Ehime University, Japan as a Ph.D. student, where he received a Doctor of Engineering (D.Eng.) in Computer Science in September 2011 for his work on facial features detection. He is currently an Associate Professor of Computer Science at the South Valley University’s Faculty of Computers and Information. His research interests include feature extraction, object detection/recognition, biometrics, image processing, computer vision, machine learning, and data hiding.
Khalid Hosny was born in 1966 in Zagazig, Egypt. He is a Professor of Information Technology, Faculty of Computers and Informatics at Zagazig University in Egypt. Prof. Hosny received his B.Sc., M.Sc. and Ph.D. degrees from the same university in 1988, 1994, and 2000 respectively. From 1997 to 1999 he was a Visiting Scholar at the University of Michigan, Ann Arbor and the University of Cincinnati in the USA. He is a senior member of ACM and IEEE. His research interests include image processing, pattern recognition, multimedia and computer vision. Prof. Hosny has published more than 60 papers in international journals, and he is an editor and scientific reviewer for more than 30 international journals.