Keywords
live aerial video, local mosaics, surveillance
Abstract
Camera-equipped mini-UAVs are popular for many applications, including search and surveillance, but video from them is commonly plagued with distracting jittery motions and disorienting rotations that make it difficult for human viewers to detect objects of interest and infer spatial relationships. For time-critical search situations there are also inherent tradeoffs between detection and search speed. These problems make the use of dynamic mosaics to expand the spatiotemporal properties of the video appealing. However, for many applications it may not be necessary to maintain full mosaics of all of the video but to mosaic and retain only a number of recent (temporally local) frames, still providing a larger field of view and effectively longer temporal view as well as natural stabilization and consistent orientation. This paper presents and evaluates a real-time system for displaying live video to human observers in search situations by using temporally local mosaics while avoiding masking effects from dropped or noisy frames. Its primary contribution is an empirical study of the effectiveness of using such methods for enhancing human detection of objects of interest, which shows that temporally local mosaics increase task performance and are easier for humans to use than non-mosaiced methods, including stabilized video.
Original Publication Citation
B. S. Morse, D. Gerhardt, C. Engh, M. A. Goodrich, N. Rasmussen, D. Thornton, and D. Eggett. Application and Evaluation of Spatiotemporal Enhancement of Live Aerial Video using Temporally Local Mosaics. Proceedings of CVPR 28: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 28, Anchorage, Alaska.
BYU ScholarsArchive Citation
Eggett, Dennis; Engh, Cameron; Gerhardt, Damon; Goodrich, Michael A.; Morse, Bryan S.; Rasmussen, Nathan; and Thornton, Daniel, "Application and Evaluation of Spatiotemporal Enhancement of Live Aerial Video using Temporally Local Mosaics" (2008). Faculty Publications. 184.
https://scholarsarchive.byu.edu/facpub/184
Document Type
Peer-Reviewed Article
Publication Date
2008-06-01
Permanent URL
http://hdl.lib.byu.edu/1877/2369
Publisher
IEEE
Language
English
College
Physical and Mathematical Sciences
Department
Computer Science
Copyright Status
© 2008 Institute of Electrical and Electronics Engineers
Copyright Use Information
http://lib.byu.edu/about/copyright/