pietikäinen matti (33 Ergebnisse)

Hardcover. Zustand: Très bon. Ancien livre de bibliothèque. Jaquette abîmée. Edition 2000. Tome 40. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Damaged dust jacket. Edition 2000. Volume 40. Ammareal gives back up to 15% of this item's net price to charity organizations.

Hardcover. Zustand: Very Good. 1st Edition. Text in English. 231 pp. Bumped corners. Slightly crooked spine.

Hardcover. Zustand: Near Fine. 1st Edition. Text in English. 231 pp. Small bump in one corner. Comes in a slipcase.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. pp. viii + 261 + 8 Illus.

Zustand: New. In.

Zustand: New. In.

Glazed Boards. Zustand: VG. 1st. Heavilly illustrated fleet history of all the vessels owner or managed by this Finnish shipping line over 50 years. 252pp. VG copy in glazed boards. Scarce.

; hardcover; quarto; ills. in b&w; name index; 231 pp. Fine copy.

Hardcover. Zustand: Brand New. 222 pages. 9.10x6.10x0.50 inches. In Stock.

Paperback. Zustand: Brand New. 2011 edition. 220 pages. 9.25x6.10x0.54 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications.Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.

Zustand: Very Good. Text in English. 575 pp. Also on the cover: 100 years 1st May 2011, Thominvest 1911-2011. On the first empty page there is greetings written by the author. Overall in a good condition. Few scratches on the covers. Thom Companies started their business as shipowners on 1 December 1957, when Thombrokers purchased its first own ship the Make. This period lasted for almost 50 years, as the last involvement in ships, a small share in a German part owners company was sold on 15 October 2007. In addition to Finnish companies there were shipowning subsidiaries in Sweden, Norway, Germany and the Cayman Islands. Ships of Thom Companies sailed under nine different flags. The name of the book 'From High Arctic to Antarctica' reflects the dimensions of the area where the ships of Thom Companies have operated. No other Finnish vessel has reached such northern latitude in the Canadian High Arctic as the Finntimber, and no other Finnish cargo vessel than the Finnpolaris has ever visited Antarctica.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications.Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.

Karton. Zustand: Sehr gut. Zust: Gutes Exemplar. Mit Vorbesitzereintrag. mit zahlreichen Abbildungen, 229 S. Schwedisch 1150g.

Hardcover/Pappeinband. Zustand: Gut. 119 Seiten The centenary fleet list of the ships owned by Bore and Rettig companies 1897-1997. Matti Pietikäinen in cooperation with Bengt Sjöström and Raimo A. Wirrankoski. Sehr gutes Exemplar, Hardcovereinband schwach fleckig. 18 Sprache: Englisch Gewicht in Gramm: 550.

Glazed Boards. Zustand: Fine. 1st. Heavilly illustrated fleet history of all the vessels owner by this Finnish shipping line over 100years. 119pp. Fine copy in glazed boards.

Hardcover. Zustand: Brand New. 257 pages. 8.50x6.25x0.75 inches. In Stock.

Zustand: New. In.

Zustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.

Gebunden. Zustand: New. A study of texture analysis in machine vision. It contains extended and revised versions of papers presented at a workshop held at the University of Oulu, Finland, in 1999. The first part of the book deals with texture analysis methodology, while the second.

Zustand: New. In.

Zustand: New. In.

Buch. Zustand: Neu. Neuware - Texture analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. Texture analysis has been a topic of intensive research for over three decades, but the progress has been very slow.A workshop on ¿Texture Analysis in Machine Vision¿ was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas.

Buch. Zustand: Neu. Neuware -Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition.Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions.Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets.Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition.Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions.Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets.Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition.Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions.Topics and features: provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms; examines algorithms for clustering and segmentation, and manifold learning for dynamical models; describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction; discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy; explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data; investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets.Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval.

Paperback. Zustand: Brand New. 2011 edition. 386 pages. 9.25x6.10x0.92 inches. In Stock.

Hardcover. Zustand: Brand New. 372 pages. 9.25x6.25x1.00 inches. In Stock.