Bibliothèque de L'IMIST/CNRST

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An introduction to object recognition : selected algorithms for a wide variety of applications par Treiber, Marco Alexander. Publication : [S.l.] Springer 2010 . 220 p. , Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the field of object recognition (OR). The book presents an overview of the diverse applications for OR and highlights important algorithm classes, presenting representative example algorithms for each class. The presentation of each algorithm describes the basic algorithm flow in detail, complete with graphical illustrations. Pseudocode implementations are also included for many of the methods, and definitions are supplied for terms which may be unfamiliar to the novice reader. Supporting a clear and intuitive tutorial style, the usage of mathematics is kept to a minimum. Topics and features: presents example algorithms covering global approaches, transformation-search-based methods, geometrical model driven methods, 3D object recognition schemes, flexible contour fitting algorithms, and descriptor-based methods; explores each method in its entirety, rather than focusing on individual steps in isolation, with a detailed description of the flow of each algorithm, including graphical illustrations; explains the important concepts at length in a simple-to-understand style, with a minimum usage of mathematics; discusses a broad spectrum of applications, including some examples from commercial products; contains appendices discussing topics related to OR and widely used in the algorithms, (but not at the core of the methods described in the chapters). Practitioners of industrial image processing will find this simple introduction and overview to OR a valuable reference, as will graduate students in computer vision courses. Marco Treiber is a software developer at Siemens Electronics Assembly Systems, Munich, Germany, where he is Technical Lead in Image Processing for the Vision System of SiPlace placement machines, used in SMT assembly. 24 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Computer vision and action recognition a guide for image processing and computer vision community for action understanding par Ahad, Md. Atiqur Rahman. Publication : Amsterdam | Paris Atlantis Press. 2011 . xxi, 211 pages 24 cm. Date : 2011 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Handbook of pattern recognition and computer vision par Chen,, C. H. Publication : [S.l.] World Scientific Publishing Company 2010 . 796 p. , Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology. 25 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Human ear recognition by computer par Bhanu, Bir. Publication : [S.l.] Springer 2010 . 201 p. , At the frontier of research, this book offers complete coverage of human ear recognition. It 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. 24 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (2),

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Information theory in computer vision and pattern recognition par Escolano, Francisco. Publication : Dordrecht | New York Springer. 2009 . xvii, 355 pages, [8] pages of plates 24 cm. Date : 2009 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Machine learning for multimedia content analysis par Gong,, Yihong. Publication : [S.l.] Springer 2010 . 277 p. , This volume introduces machine learning techniques that are particularly powerful and effective for modeling multimedia data and common tasks of multimedia content analysis. It systematically covers key machine learning techniques in an intuitive fashion and demonstrates their applications through case studies. Coverage includes examples of unsupervised learning, generative models and discriminative models. In addition, the book examines Maximum Margin Markov (M3) networks, which strive to combine the advantages of both the graphical models and Support Vector Machines (SVM). 24 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Visual analysis of behaviour : from pixels to semantics par Gong, Shaogang. Publication : [S.l.] Springer 2011 . 356 p. , This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning; examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, “bag-of-words” representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes; explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines. 24 cm. Date : 2011 Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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Fundamentals of Pattern Recognition and Machine Learning / par Braga-Neto, Ulisses. Publication : . xviii-357 pages Disponibilité : Exemplaires disponibles: La bibliothèque des sciences de l'ingénieur (1),

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