These days, more and more practical applications are being developed for artificial intelligence (AI) technologies, such as computer vision and machine learning. AI has gradually spread into our daily lives: from automatic camera/audio control to facial recognition systems in mobile devices. With AI’s continued development, it’s likely that we will see AI integrated into more of our everyday experiences.
One of the biggest advantages AI has to offer is real-time object detection and recognition. An increasing number of mobile devices come with built-in cameras, making it possible for any user to capture images or videos on the spot without resorting to extra peripherals. However, these users may sometimes encounter problems in real time, such as poor image quality, inappropriate exposure or focus level setting, and so forth. Therefore, applying AI to real-time video processing will help solve these problems.
Here are five ways to apply AI to real-time video processing.
1. Capture High-Quality Images With AI Image Enhancement
The first and foremost application of AI in real-time video processing is to enhance the quality of captured images, especially if the camera has a low resolution or poor shooting angle. For example, you can point your mobile phone camera at an object that’s 30 meters away from you, but if the pixel density of your camera is low, it will be difficult to get a clear picture. AI image enhancement can help solve this problem by improving image quality and reducing noise.
2. AI Video Light Control/White Balance Adjustment With Fast Response Time
A major shortcoming of video cams that capture images in real-time is that they can’t automatically adjust for lighting. If you’re taking a video at night, the image will be dark; if you’re shooting in bright sunlight, every shot will turn out too bright. However, AI technology can analyze video light and make real-time adjustments to improve color saturation and exposure levels — without restricting users from changing camera parameters manually.
3. Fast and Accurate Face Detection With AI Facial Recognition
Being able to detect faces in real-time will allow you to take shots with proper framing, as well as adjust for additional parameters like focus level and shooting angle. There are already numerous examples of facial recognition systems appearing on mobile devices in the form of automatic camera/audio control, but with AI technology, it’s possible to do much more than that. By analyzing facial expressions of the subject — such as whether he or she is laughing, frowning, or making a goof face — you can also apply some fun effects in real-time during video recording.
4. Real-Time Object Tracking and Dynamic Scene Recognition
For those into selfies, a smartphone is all you need to capture your image. However, if you are taking pictures at a wedding or party, it’s likely that there will be other people in the frame — and these people would usually like to participate too. With AI technology, it’s possible to recognize where an object is located in the frame and capture photos of the bride, groom, or other wedding guests. In addition to still images, AI can also be used to analyze video frames in real-time — allowing you to track objects that move between shots and recognize them, even if they appear partially obscured or in shadow.
5. AI Face Recognition for Verification Purposes During Video Chat
When it comes to online chat, most users are familiar with video chatting via Skype or FaceTime. However, during the process of making a video call, how do you know that your interlocutor is really who they say they are? With AI technology, passwords and passcodes will become things of the past — as long as both parties have their faces in view of the camera, AI will be able to recognize them instantly. Furthermore, users can also set or change their own passcode for added protection — and all of this happens without either party losing sight of their interlocutor’s face.
In conclusion, AI technology has already begun to make its presence known in many industries and applications. However, as the technology continues to evolve, we’ll begin to see AI applications that are more relevant and practical in nature. Real-time video processing is still a relatively new field; however, with improvements in visual recognition algorithms and other functions for object tracking and motion detection — AI will be able to make a huge impact on this market right now.
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