Share Email Print

Proceedings Paper

Real-time unmanned aircraft systems surveillance video mosaicking using GPU
Author(s): Aldo Camargo; Kyle Anderson; Yi Wang; Richard R. Schultz; Ronald A. Fevig
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Digital video mosaicking from Unmanned Aircraft Systems (UAS) is being used for many military and civilian applications, including surveillance, target recognition, border protection, forest fire monitoring, traffic control on highways, monitoring of transmission lines, among others. Additionally, NASA is using digital video mosaicking to explore the moon and planets such as Mars. In order to compute a "good" mosaic from video captured by a UAS, the algorithm must deal with motion blur, frame-to-frame jitter associated with an imperfectly stabilized platform, perspective changes as the camera tilts in flight, as well as a number of other factors. The most suitable algorithms use SIFT (Scale-Invariant Feature Transform) to detect the features consistent between video frames. Utilizing these features, the next step is to estimate the homography between two consecutives video frames, perform warping to properly register the image data, and finally blend the video frames resulting in a seamless video mosaick. All this processing takes a great deal of resources of resources from the CPU, so it is almost impossible to compute a real time video mosaic on a single processor. Modern graphics processing units (GPUs) offer computational performance that far exceeds current CPU technology, allowing for real-time operation. This paper presents the development of a GPU-accelerated digital video mosaicking implementation and compares it with CPU performance. Our tests are based on two sets of real video captured by a small UAS aircraft; one video comes from Infrared (IR) and Electro-Optical (EO) cameras. Our results show that we can obtain a speed-up of more than 50 times using GPU technology, so real-time operation at a video capture of 30 frames per second is feasible.

Paper Details

Date Published: 26 April 2010
PDF: 8 pages
Proc. SPIE 7668, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII, 76680S (26 April 2010); doi: 10.1117/12.849974
Show Author Affiliations
Aldo Camargo, The Univ. of North Dakota (United States)
Kyle Anderson, The Univ. of North Dakota (United States)
Yi Wang, The Univ. of North Dakota (United States)
Richard R. Schultz, The Univ. of North Dakota (United States)
Ronald A. Fevig, The Univ. of North Dakota (United States)

Published in SPIE Proceedings Vol. 7668:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII
Daniel J. Henry, Editor(s)

© SPIE. Terms of Use
Back to Top