BIAS is a biologically inspired video saliency model that integrates static and motion features via retina-like detection and multi-Gaussian fitting, outperforming baselines on DHF1K and anticipating traffic accidents up to 0.72 seconds early.
The dis- criminant center-surround hypothesis for bottom-up saliency,
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BIAS: A Biologically Inspired Algorithm for Video Saliency Detection
BIAS is a biologically inspired video saliency model that integrates static and motion features via retina-like detection and multi-Gaussian fitting, outperforming baselines on DHF1K and anticipating traffic accidents up to 0.72 seconds early.