Anomaly detection to motion direction method based on visual attention

Aiming at the disadvantage of traditional anomaly detection to motion direction such as requirement of human involvement and low intelligence, a novel detection method based on visual attention was proposed. In this method, feature maps of motion direction distributed along every orientation in space were firstly obtained by integrating the spatial and temporal derivatives of source image. On this basis, the new proposed normalization method based on area of motion field was used to endow different weight to all feature maps according to their own saliency, in order to achieve the competition among different motion direction features. The final motion saliency map could be acquired by merging all normalized feature maps. The object with obvious saliency in motion direction was focused in this saliency map, so the destination that object with motion direction saliency could be detected more effectively and intelligently from multiple moving objects.