Detection and tracking of objects based on saliency map for UAV

Abstract

Object detection and tracking is one of the most important areas of computer vision, as well as applications in unmanned aerial vehicles (UAVs). However, due to the ultra-maneuverability of the UAV mobile platform, the image in the air is usually blurry and has a low signal-to-noise ratio, which is associated with the working environment. To solve the problem of detecting ground objects on the UAV platform, traditional methods of pattern recognition and classification are often ineffective. The visual attention model is a kind of bionic vision model with good stability. In the article for the detection of ground objects using UAVs, a method based on the visual saliency model is proposed, applied to a complex terrain background for object detection. To quickly isolate terrestrial features in aerial photographs, the extracted gradient function is applied to detect an area of visual significance, and then the target image is extracted using a segmentation algorithm. The subject of the study is the method and algorithm for detecting ground objects on the map of the underlying surface using the visual saliency model and object segmentation. The object of the study is a set of video sequences of terrain maps with different terrain. The novelty of the work is an algorithm that allows detecting ground targets based on an attention map using an object segmentation algorithm. A new method for segmenting objects in a video sequence is proposed. Experimental studies were carried out on the basis of video sequences of the map of the underlying surface with different backgrounds and an analysis of the results obtained was carried out. The results obtained make it possible to identify objects in the region of interest. As a result of solving the formulated tasks, the following conclusions can be drawn: An algorithm for detecting ground objects based on an saliency map has been developed. An algorithm for segmentation of ground objects based on a gradient map has been developed. An analysis of the results of the study showed that the proposed algorithm makes it possible to detect and highlight ground objects on a map of terrain with different terrain.