Situation Graph Trees for Human Behavior Modeling

The objective of the present invention is providing a method and a simple instrument that can be used on a routine basis to accurately and quickly measure the focus position, waist radius, divergence, quality, power and power density of a laser beam. The measurement is performed by scanning a thin film of a nonlinear optical material in the focal region along the propagation direction of the beam and registering the variation of the on-axis intensity of the laser beam by a photodetector.

[1]  Hans-Hellmut Nagel,et al.  From image sequences towards conceptual descriptions , 1988, Image Vis. Comput..

[2]  Thomas B. Moeslund,et al.  A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..

[3]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[4]  Hans-Hellmut Nagel,et al.  Incremental recognition of traffic situations from video image sequences , 2000, Image Vis. Comput..

[5]  Hans-Hellmut Nagel,et al.  Image sequence evaluation: 30 years and still going strong , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[6]  Larry S. Davis,et al.  W4: Real-Time Surveillance of People and Their Activities , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Hilary Buxton,et al.  Learning and understanding dynamic scene activity: a review , 2003, Image Vis. Comput..

[8]  Tieniu Tan,et al.  Recent developments in human motion analysis , 2003, Pattern Recognit..

[9]  Hans-Hellmut Nagel,et al.  Behavioral Knowledge Representation for the Understanding and Creation of Video Sequences , 2003, KI.