Keywords
aerial surveillance, real-time, dense correspondence algorithm, graphics processing units
Abstract
Video from aerial surveillance can provide a rich source of data for many applications and can be enhanced for display and analysis through such methods as mosaic construction, super-resolution, and mover detection. All of these methods require accurate frame-to-frame registration, which for live use must be performed in real time. In many situations, scene parallax may make alignment using global transformations impossible or error-prone, limiting the performance of subsequent processing and applications. For these cases, dense (per-pixel) correspondence is required, but this can be computationally prohibitive. This paper presents a hierarchical dense correspondence algorithm designed for implementation on graphics processing units (GPUs). Since the method does not rely on epipolar geometry, it is also suitable for use when there are uncorrected nonlinear lens distortions. A framework for using this dense correspondence to implement local mosaicking, super-resolution enhancement, and mover detection is also presented and demonstrated using examples of each of these types of enhancement and different types of video sources.
Original Publication Citation
S. Cluff, B. Morse, M. Duchaineau, and J. Cohen, "GPU-accelerated hierarchical dense correspondence for real-time aerial video processing," in IEEE Workshop on Motion and Video Computing (WMVC), December 29.
BYU ScholarsArchive Citation
Cluff, Stephen; Morse, Bryan S.; Cohen, Jonathan D.; and Duchaineau, Mark, "GPU-Accelerated Hierarchical Dense Correspondence for Real-Time Aerial Video Processing" (2009). Faculty Publications. 114.
https://scholarsarchive.byu.edu/facpub/114
Document Type
Peer-Reviewed Article
Publication Date
2009-12-01
Permanent URL
http://hdl.lib.byu.edu/1877/2476
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Copyright Use Information
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