Suspicious Object Recognition Method in Video Stream Based on Visual Attention

TL;DR

This paper introduces a novel visual attention-based method for object recognition in videos, improving speed and accuracy for surveillance applications by combining bottom-up and top-down attention mechanisms.

Contribution

It presents a revised PFT method for bottom-up attention and integrates IOR and feature matching to enhance suspicious object detection in video streams.

Findings

High accuracy in object recognition demonstrated on test videos

Faster processing speed compared to traditional methods

Effective in security and surveillance applications

Abstract

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.