Definition of video recognition and its value in business
In this article, we provide a definition of video recognition and describe its main uses and value in business.
But before diving into the topic, we want to give you more context about the major technologies around it. So, we start with artificial intelligence. According to Gartner (1), “Artificial intelligence (AI) applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions”.
AI is built upon so-called core technologies, which constitute the foundations of all AI solutions. Computer vision is one of the core AI technologies. In a previous blog post, we introduced computer vision and defined it as “the art and science of making computers understand images”. We then further elaborated on image recognition.
Today, we examine another strictly related technology: video recognition.
What is it?
Video recognition can be defined as follows : it is the computer’s ability to acquire, process, and analyze data coming from visual sources, i.e. videos. In other words, it allows a computer to “see” thousands of video streams and “understand” the information it receives frame by frame.
Video tracking is one of the main differences between image and video recognition. Specifically, it consists of locating moving objects over time using a camera to associate target objects in consecutive video frames. For more details, read our post on the Multi-Object Tracking (MOT) system we developed.
Let’s go back to the technology behind it. Video recognition, like computer vision, relies on deep learning. As we wrote in a previous post, the idea of machine learning is to map some kind of input into an output. More specifically, we ask a question, input, and the algorithm provides us with an answer, output. The artificial neural networks provide the answers to your questions.
Video recognition in use
Suppose you are the manager of one, or several, car parks. You want to reduce fraud and threats, including violent behavior, the possible presence of weapons, and attempted thefts. Video recognition may be the solution.
Indeed, you might equip your surveillance cameras with a video recognition system trained to detect one of these abnormal situations. The video streams will be your input. When smart cameras detect an abnormal situation, the software will deliver an output. The output will specify, with a given level of confidence, whether there is fraud or threat or not.
The value of the technology in business
But what is the purpose of knowing there is a fraud or threat if you do not take any action?
First, the beauty of video recognition is that these analyses are performed in real-time! In addition, technologies like Deepomatic’s allow you to tailor a video recognition application to your business needs. In turn, this enables you to intervene immediately and adopt different measures according to the specific situation. As for the example above, you might call the police or intervene directly to prevent any damage.
In conclusion, this technology can detect any type of objects that appear in your videos. Therefore, it is not surprising that it is now extensively used in various fields and industries. Among others, these include safety and security, construction, and transportation.
(1). “Artificial Intelligence (AI).” Gartner IT Glossary, 15 Jan. 2019, Retrieved from www.gartner.com/it-glossary/artificial-intelligence/.