Paper
4 May 2006 Using GPU-generated virtual video stream for multi-sensor system
Author Affiliations +
Abstract
Security and intelligence services are increasingly turning toward multi-sensor video surveillance which requires human ability to successfully fuse and comprehend the information provided by videos. A training system using the same front end as real multi-sensor system for users can significantly increase such human ability. The training system always needs scenarios replicating stressful situations which are videotaped in advance and played later. This not only puts a limitation on the training scenarios but also brings a high cost. This paper introduces a new framework, virtual video capture device for such training system. Using the latest graphics processing units (GPUs) technology, multiple video streams composed of computer graphics (CG) are generated on one high-end PC and ublished to a video stream server. Thus users can be trained using both real video streams and virtual video streams on one system. It also enables the training system to use real video streams incorporating augmented reality to improve situation awareness of the human.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dezhi Liao and Brian Hennessey "Using GPU-generated virtual video stream for multi-sensor system", Proc. SPIE 6227, Enabling Technologies for Simulation Science X, 622702 (4 May 2006); https://doi.org/10.1117/12.665160
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Video surveillance

Sensors

Video acceleration

Cameras

Image processing

Image sensors

RELATED CONTENT

The future of consumer cameras
Proceedings of SPIE (March 16 2015)
NV-CMOS HD camera for day/night imaging
Proceedings of SPIE (June 09 2014)
High dynamic range adaptive real time smart camera an...
Proceedings of SPIE (April 30 2015)
Robust illumination-invariant tracking algorithm based on HOGs
Proceedings of SPIE (September 22 2015)
Real-time implementation of image alignment and fusion
Proceedings of SPIE (March 28 2005)

Back to Top