基于协同感知的视觉选择注意计算模型

鉴于在任务相关的视觉注意中,需要建立基于任务的视觉注意显著图来引导视觉注意,为此利用与人认知过程相接近的协同感知理论来研究基于任务的视觉注意计算模型,即首先利用协同识别理论研究二义及多义模式的视觉感知,得到协同视觉感知理论;然后将协同视觉感知中的模式与从视觉注意模型中提取的底层视觉特征相对应,利用偏置矩阵的性质计算底层视觉特征间受任务影响而产生的偏置,再由此偏置和底层视觉特征生成基于任务的视觉注意显著图;最后提出了基于协同感知理论的视觉选择注意计算模型。该算法用于基于任务的视觉搜索的实验结果表明,该算法是有效的,在认知上是合理的。

Visual Selective Attention Computational Model Based on Synergetic Perception

In the task-relevant visual attention, the saliency map based on task is required to be built to direct the visual attention. The synergetic perception theory which is similar to the cognition of the human is utilized to research the computational model of task-relevant visual attention. Firstly, the perception of ambiguous model is researched through the synergetic recognition theory. The synergetic visual perception theory is available. The patterns in the synergetic visual perception are corresponding to the visual features in the visual attention model. Then, the bias between the visual features influenced by the task is computed by the property of the bias matrix. The task-relevant visual attention saliency map is built from the bias and the visual features. Finally, a computational model of visual selective attention based on synergetic perception is presented. The algorithm is applied to the visual search task. The validity and the rationality in cognition of the algorithm are demonstrated through the experiments.