Over recent years the use of Artificial Intelligence (AI) and machine learning have grown and developed significantly, slowly broadening horizons being used in many different industries.
What is Machine Learning?
Machine learning is an application of artificial intelligence (AI) that provides computer systems the ability to automatically learn and improve from experience without the need for manual programming. Machine learning focuses on the development of technology that can access data and use it to learn from.
When most people hear the terms “Artificial Intelligence” and “Machine Learning” they usually picture driverless cars and robot assistants, well these are now not the only cases of machine learning. AI technology is now being implemented in an extensive range of fields, including the video and film industry. Within this article, we are going to explore how machine learning could have an impact on the future of video creation and editing.
AI undertaking Video Tasks
Drone technology has been advanced to now be used in the process of filming, to improve the quality and accuracy of film footage. Modern drones are capable of increasing the efficiency and accuracy of camera work.
The latest technology enables drones to follow a subject automatically with no need for any human assistance and to keep the subject perfectly centered in the frame at all times. This technology has also been advanced to avoid obstacles through the use of multi-directional sensors without the need for human intervention.
Machine learning combined with AI technology is now more than adequate to complete tasks in just a small portion of the time required for a person to undertake the same task.
This is especially true when it comes to the process of tagging and cataloging video footage. Through the use of Machine Learning combined with manual processes, metadata can be tagged and recorded to a workstation at a much quicker rate than ever before, but can also be auto-tagged using an object, face, and location recognition technologies, thereby enhancing the quality and accuracy of metadata to increase the power of content discovery.
Machine learning and AI can ‘decode’ and ‘interpret’ video footage which means they can play a huge role in the video editing field. From visual effects right through to image stabilization these tools will be using complex algorithms to attempt to analyze videos in the same way in which they do with images.
All of the video editing advancements are a machine learning tool to assist and facilitate a human editor rather than to replace it. However, in the future, AI could possibly have the ability to edit videos fully automatically with no need for human intervention but this could be a while away yet.
One of the earliest examples of machine learning and AI in the video editing industry was in 2016 when IBM used a “supercomputer” to curate footage and create a trailer for the horror film Morgan. Machine learning was used to analyze other trailers and then applied this information to curate and select scenes from the film that would be best for the trailer. Usually creating a film trailer would take hours of an editor’s time to analyze and watch all the available film footage whereas the use of machine learning to curate video footage dramatically over halved the time required to do this.
Another example of video curation is by Apple after the latest IOS update the all-new Photos tab lets you browse your photo library with different levels of curation, so it’s easy to find, relive and share your photos and videos. You can view everything in All Photos, focus on your unique photos in Days, relive your significant moments in Months or rediscover your highlights in Years.
While AI-based video editing is still in the early stages of development the progress that has been made in the last year is exceptional. However, it will still be some time before this technology and machine learning starts to make an appearance in commercial video editing. Although there is no doubt that AI is transforming video editing so far all of its advancements to date are tools to assist and facilitate a human video editor rather than to replace.