Machine learning vision based motion (25 risultati)

Lingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
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Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2013
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Altre immaginiLingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Taschenbuch. Condizione: Neu. Machine Learning for Vision-Based Motion Analysis | Theory and Techniques | Liang Wang (u. a.) | Taschenbuch | Advances in Computer Vision and Pattern Recognition | xiv | Englisch | 2013 | Springer | EAN 9781447126072 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 6912…1 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Lingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Lingua: Inglese
Editore: Springer London, Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: 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.

Lingua: Inglese
Editore: Springer London, Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: 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 interf…aces, 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.

Lingua: Inglese
Editore: Springer, 2012
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 2011 edition. 386 pages. 9.25x6.10x0.92 inches. In Stock.

Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Lingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
- Rilegato
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Lingua: Inglese
Editore: Springer London, Springer London Jan 2013, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 388 pp. Englisch.

Lingua: Inglese
Editore: Springer London Nov 2010, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
- Rilegato
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - 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 huma…n-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. 388 pp. Englisch.

Lingua: Inglese
Editore: Springer London, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive and accessible review of vision-based motion analysisHighlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspectiv…eDescribes the benefits of collaboration .

Lingua: Inglese
Editore: Springer London, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive and accessible review of vision-based motion analysisHighlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspectiv…eDescribes the benefits of collaboration .

Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 388.
Altre immaginiLingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: preigu, Osnabrück, Germaniapreigu
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Buch. Condizione: Neu. Machine Learning for Vision-Based Motion Analysis | Theory and Techniques | Liang Wang (u. a.) | Buch | Advances in Computer Vision and Pattern Recognition | xiv | Englisch | 2010 | Springer | EAN 9780857290564 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg,…juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Lingua: Inglese
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Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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-ma…chine 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.

Lingua: Inglese
Editore: Springer London, Springer Jan 2013, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 160,49
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 h…uman-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.

Lingua: Inglese
Editore: Springer, 2013
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Condizione: New. PRINT ON DEMAND pp. 388.

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Condizione: New. Print on Demand pp. 388 Illus.

Lingua: Inglese
Editore: Springer, 2010
Serie: Libro 17 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 388.