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Video Enhancement AI Algorithms – Creating Professional-Grade Video Quality from a Front-Facing Smartphone Camera

AI algorithms are giving front-facing smartphone cameras a much-needed boost, and the timing couldn’t be better.

Artificial intelligence has played a crucial role throughout the pandemic. From real-time disease monitoring to insights for businesses forced to embrace a more digital structure, AI has been largely helpful as our world has rapidly changed. Similarly, AI is also playing a role in smartphone video – which has been vital in connecting individuals with loved ones and coworkers throughout the pandemic.

Social distancing has left people physically isolated from their friends, family and coworkers. Fortunately, our communication with these individuals has not wavered. Thanks to video communication programs like Zoom and FaceTime, and video-based social media apps like Instagram and Snapchat, we’ve been able to consistently communicate with everyone we typically would on a day-to-day basis pre-pandemic, from a smartphone.

However, with the rise of video communication came some technical difficulties. By this point, everybody has experienced the usual suspects of bad video quality – lagging, shaking, and face distortion. While video collaboration apps have enabled people to communicate on smartphones while social distancing, poor smartphone video quality prohibits this communication from being easy and seamless.

Enter artificial intelligence. As video-based content creation and communication continue their proliferation, video enhancement software companies are using AI algorithms to develop tools that will unleash the next wave of creativity and human connection.

Stabilizing the Selfie

The infamous selfie video is a prominent part of modern communication, both at work and in private life. Prone to distortion, unreliable quality and non-centered faces, selfie video could certainly use an upgrade, especially with its increased usage in recent years. By leveraging facial recognition, artificial intelligence and machine learning technologies, video enhancement software makes it easier to overcome these bothersome issues.

Shaky video quality can disrupt essential phone calls with relatives, friends, and business colleagues. Eliminating this shakiness is the key to unlocking on-the-go video communication. Software stabilization algorithms provide a solution by combining sensor data from the smartphone’s gyro with the patented stabilization IP and applying frame-to-frame video stabilization in the form of cancellation of unintended movement between frames. In this way, AI algorithms make handheld video recordings invincible to involuntary motion, wobbling and swaying.

This also helps in keeping the camera focused on the user’s face. Whether users are capturing a memory or communicating with others, selfie videos can be hard to control, as faces slip in and out of the video window. However, using video enhancement algorithms, software detects the user’s face and applies algorithms to track its movement and reposition it within the frame, even in low-light conditions.

Video enhancement algorithms allow the user to focus on the conversation rather than technical issues by providing impressive face stabilization and face distortion removal, which effortlessly gives any selfie video a noticeable quality boost.

The Future of AI and Video Enhancement Algorithms

In the coming years, I expect video processing algorithms to see dramatic growth. By using new data to fine-tune video stabilization algorithms, video enhancement software can be improved continuously. With increased customization flexibility and more advanced compression, smartphones will be able to adapt file sizes for rapid sharing and transmission, for smartphone selfie videos or even drone footage in the 5G world.

These algorithms can find the region of interest in videos, and in the future, they’ll automatically zoom in and intelligently focus on what they’re seeing: a goal being scored at a soccer game, the birthday cake candles being blown out, or the moment the beat drops in the club.

The next wave of video creation will likely be a community effort, using data to blend video from multiple smartphones into one finished product intelligently. For example, imagine a wedding with 200 guests and nearly as many smartphones all recording the event. An individual, group, or family can record the same event and quickly generate a polished-looking video with multiple angles, effects, transitions, and more. Eventually, an even larger crowd — friends and strangers — will be able to simultaneously share smartphone video from a concert, party, rally, or other gathering and have it stitched together to tell visual stories no one has been able to tell before without considerable effort.

The future is bright for video enhancement algorithms, and thus, promising for smartphone camera quality as a whole.

About the Author

Andreas Lifvendahl holds a MSc degree in Electrical Engineering from Uppsala University, Sweden. Andreas has worked in a number of senior business roles, bringing Swedish technology from smaller firms to the global stage, spanning industries such as medical devices, semiconductors and embedded systems. Since 2012, Andreas is CEO of Imint, and in addition aids other technology companies as board member or business advisor.

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