Learned Linear Models for Detecting Watercraftin a Maritime Environment
2020
This work provides a new, to the best of our knowledge, approach to
constructing linear models for object detection in a scene. Specifically,
we use representative training data in order to estimate the parameters
describing a generalized wavelet model for the express purpose of
detecting the presence of maritime targets in a scene. The parameter
estimates are taken as those that maximize the probability of detecting
the targets for a fixed probability of false alarm. The approach is then
demonstrated on a database of short-wave infrared imagery containing
various watercraft. Results are then compared to some of the more standard
wavelet bases used in detection applications.
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