動的ベイジアンネットワークを用いた視覚的注意の確率モデル(一般,膨大なデータから学ぶもの) A stochastic model of selective visual attention with a dynamic Bayesian network

Recent studies in signal detection theory suggest that the human responses to the stimuli on a visual display are non-deterministic. People may attend to different locations on the same visual input at the same time. To predict the likelihood of where humans typically focus on a video scene, we propose a new stochastic model of visual attention by introducing a dynamic Bayesian network. When describing the network of visual attention, the principle of the signal detection theory is introduced, namely, the position where a saliency response takes the maximim is the eye focusing position. Experimental results have demonstrated that our model performs significantly better in predicting human visual attention compared to the previous deterministic model.