IndexIntroductionConclusionUsual Traditional ApproachesSummary: Video surveillance is a highly debated topic across the world due to its various applications in several important fields such as security, traffic cameras, banking, museums, educational institutions and many other fields. The main problem behind this “video surveillance” is the movement of objects. Moving object detection refers to the idea of ​​identifying the physical movement of an object in a certain area. For the detection of moving objects, the current frame and the background frame of a video sequence are taken into account. This article attempts to give a review of notable and mentionable ongoing and past works on moving object detection. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Introduction Video is an electronic medium for recording, copying, playing, transmitting, and displaying moving visual media. Surveillance refers to the close observation of a person or object with the intent to influence, manage, direct, and protect. Video surveillance is equipment that enables integrated image capture capabilities that allow you to compress, store or transmit video images or extracted information over communications networks or digital data links. A video is basically a group of frames where the frame can be defined as one of many still images that combine into the total moving image. Moving object detection is the concept of differentiating stationary objects from moving or non-stationary objects over a given region or area. There are basically 3 steps in video analytics: identification, tracking and analysis. And as we can see, this is not possible without moving object detection. Moving object detection has become a very serious topic for researchers, scientists and indeed anyone working with video surveillance and analytics. The main reason for this is the application of moving object detection in various and large fields. We can mention some fields such as video surveillance, airport security monitoring, law enforcement, video compression, automatic target identification, marine surveillance, radar system, theft prevention, department stores and many other areas. There are many techniques used for moving object detection, but some such as background subtraction, frame differencing, temporal differencing, and optical flow can be specially mentioned due to their wide usage as traditional methods. But each of these techniques has disadvantages associated with it. Even though new techniques are invented and applied every day, it is still a challenging task due to dynamic background, lighting variations, misclassification of shadows as objects, camouflage, and bootstrapping issues. A lot of research is being conducted regarding these issues which this article attempts to shed light on. The remainder of this article is indexed as follows: Section II. Usual traditional approachesSection III. Recent ResearchConclusionUsual Traditional ApproachesThe following figure will attempt to classify and categorize moving object detection approaches.A. Frame DifferentiationFrame Differentiation, as the name suggests, detects the moving object by distinguishing between two consecutive frames. Subtracts the second frame from the first frame of the image using the of operator.