As the name suggests, object detection is a phenomenon used to spot different objects in image frames. Object detection is a product of Computer Vision and is a very effective technique to precisely locate items of different shapes and sizes and label them. What is Object Detection? Object detection is a way to provide computers with a set of eyes. Once applied, computers can quickly identify objects just like humans do and use different operations based on the presence of specific objects in the frame. For example, imagine you have an image of a road on a busy day, and you want your computer to be able to label the different kinds of vehicles in the photo. Once you input that photo to an object detector such as , it will instantaneously the vehicles present on the road, as well as any human or other animal present inside it. YOLO locate and label However, it's essential to realize that an object detector will only detect the objects it's trained to. For example, suppose you're using a custom object detector that's only trained to spot and label dogs. In that case, it won't magically label everything in the images provided and will only label dogs. Object Detection Vs. Image Recognition An essential difference worth mentioning here is between Object Detection and Image Recognition since most people confuse the two. Image recognition only predicts what object is present inside a frame and prints it along with the picture, while object detection labels each instance of an object inside the frame by using a . bounding box For example, if two cats are in a frame, the object detector will draw bounding boxes around both cats and label them using their exact coordinates. At the same time, the image recognition will only print 'Cat' along with the frame, no matter how many cats are in the photo. Source Object Detection Use Cases Now that we have a sound knowledge of object detection, let's move forward and see some actual use cases. We’ll go through each application one-by-one, discussing the implementations in detail. Self-Driving Cars Let's start with the most significant and most revolutionary use-case of object detection in the tech world – self-driving cars. Real-time object detection has always played a crucial part in the world of self-driving vehicles. Autonomous vehicle systems use high accuracy object detectors that work in real-time to spot any objects on the road to let the car drive safely. The object detectors used by self-driving cars are state-of-the-art and can even classify stationary or moving objects. While there are many other things as well that go into the making of self-driving vehicles, object detection sits at the core of it. In a nutshell, the process breaks down into three categories: localization, mapping, and tracking. Localization refers to figuring out the vehicle's position relative to the environment; mapping refers to taking the context of the environment into account. Finally, tracking means identifying moving objects to plan the path of the vehicle. 2. Mask Detection Mask detection has probably been the most sought-after use case of object detection in the past year. Ever since the pandemic has broken out, businesses have been implementing mask detectors in their buildings to spot people violating the regulation of wearing masks. Right now, many malls and shopping centers are using object detectors to implement mask detection systems to ensure the safety of customers and staff members. Once you learn how to train your custom object detectors, implementing a face mask detector isn't that hard! All you've got to do is find a suitable dataset, and then you're good to go. There are various available on the internet as well if you need a start. tutorials 3. Video Surveillance Since the top-notch object detectors are highly accurate and can label multiple instances of objects in a single frame in real-time, they're highly effective tools when it comes to video surveillance. Video frames are sequentially fed to the object detectors, and each frame can be used to spot any abnormal activity, given the high-quality video input. Many warehouses, banks, and retail stores are currently employing object detectors in their video surveillance cameras. Whenever something irregular or alarming pops up, the relevant authorities are automatically alarmed by the surveillance systems. 4. Crowd Counting Source This is yet another vital scenario when it comes to post-pandemic times. Due to the safety of crowds in places like malls, it's essential to avoid many people getting together in tight spots. Crowd counting systems use object detectors to measure how many persons are present in a given area and the density of people in a particular location. Consequently, highly crowded places can be automatically spotted by the object detector without anybody manually interfering. So, you see, object detectors are not only used to identify and localize objects in a given frame, but they can also calculate the proximity between particular objects and calculate the distances between them. 5. Anomaly Detection Anomaly detection is a simple yet compelling use case of object detection applied in a wide variety of industries. It works differently given the specific industry. Industries that produce goods or process raw material often have to go through materials that have expired or gone wrong, and not being able to spot those materials could prove to be disastrous. For example, in the agriculture industry, a object detector could identify plants that have been affected by a disease. While farmers could manually do this as well, they might not be very accurate and end up wasting a lot of time. custom-trained While this process used to be wholly manual and many human resources were wasted in this, object detection has completely revolutionized the process. The automated systems are not only fast, but they're also highly cost-effective once they're developed. 6. Media & Entertainment As surprised as you might be, the media & entertainment industry has also started to get around the use of object detection in its daily business. Sports matches such as football and rugby are amongst the first ones to use object detection; in fact, NFL uses real-time object detection to track the football in a match. Not only does this make the analysis easier, but it also makes tracking the ball easier when it’s surrounded by a lot of players and no single camera angle is enough to spot it fully. Moreover, the sports-betting industry also uses object detection heavily to obtain information efficiently, making the analysis much faster and accurate. 7. Medical Image Analysis Last but not least, the has also seen some huge benefits from object detection, such as medical image analysis. Medical imaging such as ultrasounds produces a heavy amount of visual data that needs to be analyzed in detail to diagnose issues with the patients. health industry Custom-trained object detectors are great in spotting minor details, saving considerable time for the surgeons. According to an estimate, radiologists go through around 200 medical images per day. Imagine the time they would save if a certain amount of their work were automated. Wrap Up Object detection is a crucial and highly developing technique that comes under the hood of computer vision. While the technique is directly linked to data availability and processing speed, it has been making fantastic progress in the past decade, given the abundance of data and highly increasing processing capabilities. Throughout the article, we have gone through some of the most important applications of object detection that are currently being applied in different sectors. As you can see, giving a computer ‘a set of eyes’ could prove to be very beneficial to humans in almost every field of life.

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