Abstract:
Remote sensing, early warning systems, and visual tracking use small aerial object detection. Existing moving object detection methods can distinguish normal-sized objects from the dynamic background, but not small ones. A novel method is proposed for accurate small aerial object detection under different situations. Block segmentation reduces frame information redundancy initially. A random projection feature (RPF) characterizes blocks into feature vectors. Next, feature vectors are used to measure block motions and filter out major directions. Finally, variable search region clustering (VSRC) and color feature difference extract pixelwise targets from moving direction blocks. Our approach outperforms state-of-the-art methods on small aerial object integrity, especially on dynamic background and scale variation targets, according to comprehensive experiments.
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