Visual surveillance transformer

Abstract

In the case of the unmanned surveillance system field, even if it is the same object, the detection result will be different depending on the state of the object and the configuration of the surrounding environment. Therefore, artificial intelligence for unmanned surveillance needs to understand the environment on the image, understand the state of the object within the image, and understand the relationship between them. For this purpose, in this study, a transformed transformer structure that can receive a single image, which is 2D data, as an input, unlike splitting one image into a certain size and using it as an input, is presented, and the effect between neighboring pixels is considered by using a segmentation model to which it is applied. A possible background classification model was constructed.