Machine learning for vision-based motion analysis : theory and techniques / Liang Wang [and others], editors.
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...
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| Format: | Ebook |
| Language: | English |
| Published: |
London :
Springer,
[2011]
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| Series: | Advances in pattern recognition.
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| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | 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 In. |
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| Physical Description: | 1 online resource (xiv, 372 pages) : illustrations. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 0857290568 9780857290564 0857290576 9780857290571 1282973088 9781282973084 |