Spatiotemporal saliency based on distributed opponent oriented energy

A computational saliency model utilizing bio-inspired features for spatiotemporal saliency is presented in this paper. We first propose distributed opponent oriented energy for compact local dynamic texture description motivated by Human Vision System. Then, we integrate the derived motion characterization and a revised self-resemblance saliency framework. High effectiveness and efficiency of the proposed method is extensively demonstrated both qualitatively and quantitatively, for background subtraction in the cases of extremely dynamic scenes and camera jitter. In terms of the trade-off between accuracy and computation cost, our method achieves competitive results in contrast to the state-of-art algorithm.