利用心理学中有关视觉注意的研究成果,提出一种新的动态场景中的视觉注意区域检测算法.该算法利用视觉对场景的感知的特点,以特征点轨迹作为运动特征,计算特征点运动的显著性,并用运动显著的特征点作为“种子”,结合空间分割方法产生运动显著图.为了兼顾静态场景,则利用颜色和亮度作为特征,以center-surround反差模型获得图像的静态显著图.最后提出一种基于运动优先思想的方法将运动和空间显著图进行动态融合。生成视觉注意区域.与以往方法相比。该方法生成的视觉注意区域较为完整,并且具有更好的抗噪性.实验结果证明了该方法的有效性和稳定性.
Proposed a novel visual attention regions detection method in dynamic scene which employs the spatiotemporal model.With the properties of Human Visual System(HVS),the motion attention is computed from the homography of feature points trajectory.The static attention map is generated using center-surround descriptor.At last,the spatial and motion attention are combined to form an overall attention map in a motion priority fashion.Experimental results show that our proposed method is capable of achieving both good accurate and the stable performance.