Document Type
Conference Paper
Publication Date
2-2015
Publication Source
Proceedings of SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015
Abstract
There are many transportation and surveillance cameras currently in use in major cities that are close to the ground and show scenes from a perspective point of view. It can be difficult to follow an object of interest across multiple cameras if many of these cameras are in the same area due to the different orientations of these cameras. This is especially true when compared to wide area aerial surveillance (WAAS).
To correct this problem, this research provides a method to non-linearly transform current camera perspective views into real world coordinates that can be placed on a map. Using a perspective transformation, perspective views are transformed into approximate WAAS views and placed on a map. All images are then on the same plane, allowing a user to follow an object of interest across several camera views on a map. While these transformed images will not fit every feature of the map as WAAS images would, the most important aspects of a scene (i.e. roads, cars, people, sidewalks etc.) are accurate enough to give the user situational awareness.
Our algorithm is proven to be successful when tested on cameras from the downtown area of Dayton, Ohio.
Inclusive pages
94070Q-1 to 94070Q-13
ISBN/ISSN
0277-786X
Document Version
Published Version
Copyright
Copyright © 2015, Society of Photo-optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited.
Publisher
Society of Photo-optical Instrumentation Engineers
Place of Publication
San Francisco, CA
Volume
9407
eCommons Citation
Krucki, Kevin C. and Asari, Vijayan K., "Scene Projection by Non-Linear Transforms to a Geo-Referenced Map for Situational Awareness" (2015). Electrical and Computer Engineering Faculty Publications. 382.
https://ecommons.udayton.edu/ece_fac_pub/382
Comments
This document is provided for download in compliance with the publisher's policy on self-archiving. Permission documentation is on file.
DOI: http://dx.doi.org/10.1117/12.2077737