Suspicious Object Recognition Method in Video Stream Based on Visual Attention
This incremental work addresses video surveillance and security applications by improving object recognition performance.
The authors tackled the problem of recognizing suspicious objects in video streams by proposing a method based on visual attention, which enhances speed and accuracy compared to traditional methods, as shown in extensive tests.
We propose a state of the art method for intelligent object recognition and video surveillance based on human visual attention. Bottom up and top down attention are applied respectively in the process of acquiring interested object(saliency map) and object recognition. The revision of 4 channel PFT method is proposed for bottom up attention and enhances the speed and accuracy. Inhibit of return (IOR) is applied in judging the sequence of saliency object pop out. Euclidean distance of color distribution, object center coordinates and speed are considered in judging whether the target is match and suspicious. The extensive tests on videos and images show that our method in video analysis has high accuracy and fast speed compared with traditional method. The method can be applied into many fields such as video surveillance and security.