HUMAN DETECTION FOR THERMAL AND VISIBLE IMAGES

Abstract

Human detection and localization is one of the importance aspects in computer vision. It has broad applications in surveillance, robotic, driver assistance system, and for the military applications. The task is difficult because it depends on various conditions such as illumination, distance, human pose and weather condition. This study aimed to investigate human detection methods for thermal and visible images. We have explored three methods which are histogram of oriented gradient, integral image and aggregate of channel features. Our result showed that histogram of oriented gradient outperformed the other two using the tested images. However, the method is only applicable when the human is on the standing or upright position and limited to a certain distance between the scene and the camera position.