Can I read Machine Learning for Vision-Based Motion Analysis || on EtoBox?

Machine Learning for Vision-Based Motion Analysis || by Tomoya Sakai, Atsushi Imiya (auth.), Liang Wang, Guoying Zhao, Li Cheng, Matti Pietikäinen (eds.) is a nonfiction available to read on EtoBox.

What is Machine Learning for Vision-Based Motion Analysis || about?

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,

Who reads Machine Learning for Vision-Based Motion Analysis ||?

Author

Tomoya Sakai, Atsushi Imiya (auth.), Liang Wang, Guoying Zhao, Li Cheng, Matti Pietikäinen (eds.)

Publisher

Springer London : Imprint : Springer

Published

2011

Language

EN

ISBN

9780857290571

Category

nonfiction

Subjects

Computer Science, Science, Engineering