Hardware Design Optimization for Human MotionTracking Systems: A stochastic framework for evaluating and comparing the expected performance of sensing systems for interactive computer graphics - Tapa blanda

Allen, B. Danette

 
9783639137255: Hardware Design Optimization for Human MotionTracking Systems: A stochastic framework for evaluating and comparing the expected performance of sensing systems for interactive computer graphics
Tapa blanda
ISBN 10: 3639137256 ISBN 13: 9783639137255
Editorial: VDM Verlag Dr. Müller, 2009

Sinopsis

This research introduces a stochastic framework for evaluating and comparing the expected performance of sensing systems for interactive computer graphics. Incorporating models of the sensor devices and expected user motion dynamics, this framework enables complementary system- and measurement-level hardware information optimization, independent of algorithm and motion paths. The approach for system-level optimization is to estimate the asymptotic position and/or orientation uncertainty at many points throughout a desired working volume or surface, and to visualize the results graphically. This global performance estimation can provide both a quantitative assessment of the expected performance and intuition about how to improve the type and arrangement of sources and sensors, in the context of the desired working volume and expected scene dynamics. Using the same model components required for these system-level optimization, the optimal sensor sampling time can be determined with respect to the expected scene dynamics for measurement-level optimization.

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Reseña del editor

This research introduces a stochastic framework for evaluating and comparing the expected performance of sensing systems for interactive computer graphics. Incorporating models of the sensor devices and expected user motion dynamics, this framework enables complementary system- and measurement-level hardware information optimization, independent of algorithm and motion paths. The approach for system-level optimization is to estimate the asymptotic position and/or orientation uncertainty at many points throughout a desired working volume or surface, and to visualize the results graphically. This global performance estimation can provide both a quantitative assessment of the expected performance and intuition about how to improve the type and arrangement of sources and sensors, in the context of the desired working volume and expected scene dynamics. Using the same model components required for these system-level optimization, the optimal sensor sampling time can be determined with respect to the expected scene dynamics for measurement-level optimization.

Biografía del autor

Dr. B. Danette Allen is a senior researcher at NASA Langley Research Center. She has extensive experience in the design and development of atmospheric science instruments and is investigating methods for modernizing the National Airspace System. Dr. Allen received her Ph.D. in Computer Science from the University of North Carolina at Chapel Hill.

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Editorial
VDM Verlag Dr. Müller
Año de publicación
2009
Idioma
Inglés
ISBN 10 
3639137256
ISBN 13 
9783639137255
Encuadernación
Tapa blanda
Número de páginas
196
Contacto del fabricante
no disponible
Persona responsable
no disponible