Performance Indicator Survey for Object Detection
In Ho Park, Sungho Kim
Abstract
In recent image processing, beyond the object recognition problem, deep learning has been used in various aspects such as object detection, semantic segmentation. In addition, classic technique-based detection has been performed variously. These technologies are applied in various systems such as factory automation systems, automatic target recognition (ATR) systems, autonomous driving systems, etc. Object detection is performed in various categories such as people, vehicles and animals, etc. And it is operated for various situations which contain different object size, image size, distance range from near to remote, changeable environment, etc. For the situation analysis, indicators need to be used appropriately. And when researchers make some algorithm for object detection, if there are no any evaluation indicators, the algorithm can't be demonstrated. So, it is important to know about performance indicators of object detection. Various indicators are used in object detection. As a result, this paper introduces performance indicators of object detection. The main purpose of the survey is that researchers find the proper performance indicator for object detection. And It can help to compare the detection result with a different algorithm result, exactly and effectively.