A Review of Object Detection Techniques

Abstract

Object detection is widely used in the field of computer vision and crucial for variety of applications, e.g., self-driving car. During the development of half a century, object detection methods have been continuously developed, and generated numerous approaches which obtained promising achievements. At present, the approach of object detection has been largely evolved into two categories which are traditional machine learning methods utilizing varied computer vision techniques and deep learning method. This article presents a review of object detection techniques. Firstly, the existing methods based on traditional machine learning are summarized and introduced. Then, two main schools of deep learning methods, R-CNN and YOLO, are selected for analysis and introduction. At the end of the article, the methods mentioned are briefly compared and discussed.