Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition describes some computer vision-based methods that analyze video sequences of humans. More specifically, methods for tracking multiple humans in a scene, estimating postures of a human body in 3D in re...

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Bibliographic Details

Main Authors:	Ohya, Jun (Author), Utsumi, Akira (Author), Yamato, Junji (Author)
Format:	Electronic eBook
Language:	English
Published:	New York, NY Springer US 2002
Edition:	1st ed. 2002
Series:	The International Series in Video Computing 3
Subjects:	Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing and Computer Vision Multimedia Information Systems User Interfaces and Human Computer Interaction Optical data processing Multimedia information systems User interfaces (Computer systems) Bewegtes Bild Videobild Maschinelles Sehen Objektverfolgung
Online Access:	UBY01 Volltext
Summary:	Analyzing Video Sequences of Multiple Humans: Tracking, Posture Estimation and Behavior Recognition describes some computer vision-based methods that analyze video sequences of humans. More specifically, methods for tracking multiple humans in a scene, estimating postures of a human body in 3D in real-time, and recognizing a person's behavior (gestures or activities) are discussed. For the tracking algorithm, the authors developed a non-synchronous method that tracks multiple persons by exploiting a Kalman filter that is applied to multiple video sequences. For estimating postures, an algorithm is presented that locates the significant points which determine postures of a human body, in 3D in real-time. Human activities are recognized from a video sequence by the HMM (Hidden Markov Models)-based method that the authors pioneered. The effectiveness of the three methods is shown by experimental results
Physical Description:	1 Online-Ressource (XXII, 138 p)
ISBN:	9781461510031
DOI:	10.1007/978-1-4615-1003-1