Intelligent Vehicle Visual Navigation Algorithm Based on Visual Saliency Improvement

Abstract

The automobile has gradually developed into an indispensable tool for human daily travel and transportation. Further reducing the traffic accident rate to improve the traffic safety level and improving the road traffic safety performance is a global issue worthy of common concern for human beings, moreover, it is a common concern for political circles, scholars, researchers, and other related workers in the field of transportation all over the world. Therefore, in this paper, by studying a large amount of literature and carrying out relevant model construction, based on the theories of visual navigation basic theory, intelligent vehicle theory and visual saliency improvement theory, etc., the intelligent vehicle visual navigation with visual saliency improvement is studied in depth through the feature point tracking algorithm research method (including three feature point methods and one optical flow method), and it is concluded that the intelligent vehicle with visual saliency improvement is better than the ordinary. The conclusion that the overall performance of the vehicle is better in all aspects. The following discussions are also proposed for the algorithm improvement: acquisition of visual saliency images; continuous enhancement of visual saliency of images; reasonable application of filtering algorithm.