
Proceedings Paper
Optical flow object detection, motion estimation, and tracking on moving vehicles using wavelet decompositionsFormat | Member Price | Non-Member Price |
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Paper Abstract
Optical flow-based tracking methods offer the promise of precise, accurate, and reliable analysis of motion, but they
suffer from several challenges such as elimination of background movement, estimation of flow velocity, and optimal
feature selection. Wavelet approximations can offer similar benefits and retain spatial information at coarser scales,
while optical flow estimation increases with the reduction of finer details of moving objects. Optical flow methods often
suffer from significant computational overload. In this study, we have investigated the necessary processing steps to
increase detection and estimation accuracy, while effectively reducing computation time through the reduction of the
image frame size. We have implemented an object tracking algorithm using the optical flow calculated from a phase
change between representative coarse wavelet coefficients in subsequent image frames. We have also compared phasebased
optical flow with two versions of intensity-based optical flow to determine which method produces superior
results under specific operational conditions. The investigation demonstrates the feasibility of using phase-based optical
flow with wavelet approximations for object detection and tracking of low resolution aerial vehicles. We also
demonstrate that this method can work in tandem with feature-based tracking methods to increase tracking accuracy.
Paper Details
Date Published: 7 May 2010
PDF: 10 pages
Proc. SPIE 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR, 76941J (7 May 2010); doi: 10.1117/12.853281
Published in SPIE Proceedings Vol. 7694:
Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR
Michael A. Kolodny, Editor(s)
PDF: 10 pages
Proc. SPIE 7694, Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR, 76941J (7 May 2010); doi: 10.1117/12.853281
Show Author Affiliations
Michael P. Dessauer, Louisiana Tech Univ. (United States)
Sumeet Dua, Louisiana Tech Univ. (United States)
Published in SPIE Proceedings Vol. 7694:
Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR
Michael A. Kolodny, Editor(s)
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