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- W2034285144 abstract "Long range surveillance videos are often distorted by random perturbations of the optical pathways caused by atmospheric turbulence. While humans can easily perceive and separate the moving objects from the turbulent motion, it is still a challenge for vision systems. In this paper, we present a near real-time approach to detecting moving objects in the presence of turbulence. As a first step, our method learns the dynamics of the latent turbulence and extracts an approximate foreground. Statistical analysis of the foreground object properties is used to eliminate noise due to turbulence preserving only the true moving objects. Our approach also results in a stable background with minimal turbulence. We tested our method on a wide range of scenarios corrupted by various levels of turbulence. Compared with state of the art, our results are quite promising." @default.
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- W2034285144 date "2014-12-14" @default.
- W2034285144 modified "2023-09-24" @default.
- W2034285144 title "Robust Tracking of Objects through Turbulence" @default.
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- W2034285144 doi "https://doi.org/10.1145/2683483.2683512" @default.
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