During about 30 years, a lot of research teams have worked on the big challenge of detection of moving objects in various challenging environments. First applications concern static cameras but with the rise of the mobile sensors studies on moving cameras have emerged over time. In this survey, we propose to identify and categorize the different existing methods found in the literature. For this purpose, we propose to classify these methods according to the choose of the scene representation: one plane or several parts. Inside these two categories, the methods are grouped according to eight different approaches: panoramic background subtraction, dual cameras, motion compensation, subspace segmentation, motion segmentation, plane+parallax, multi planes and split image in blocks. A reminder of methods for static cameras is provided as well as the challenges with both static and moving cameras. Publicly available datasets and evaluation metrics are also surveyed in this paper.

在大约30年的时间里，许多研究团队都致力于应对各种挑战性环境中移动物体的检测这一巨大挑战。最初的应用涉及静态相机，但随着移动传感器的兴起，对移动相机的研究逐渐兴起。在这项调查中，我们建议对文献中发现的不同现有方法进行识别和分类。为此，我们建议根据场景表示的选择对这些方法进行分类：一个平面或多个部分。在这两个类别中，这些方法根据八种不同方法进行分组：全景背景减法，双摄像头，运动补偿，子空间分割，运动分割，平面+视差，多平面和块分割图像。提醒人们使用静态相机的方法，以及静态和动态相机的挑战。本文还对公开可用的数据集和评估指标进行了调查。