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IBM used machine learning to teach its supercomputer, Watson, how to select impactful moments from the match. If you watched highlights from the US Open recently, chances are you actually experienced the results of this new technology firsthand. The better your editing software is able to detect them automatically, the less work you’ll have to do to create a shareable video from your automated camera. If you’re passively capturing hours of footage, finding highlights could take a really long time. If the camera is operating on its own, you won’t have that important feedback, meaning you’ll have to sift through all the footage manually. A good operator will note highlights, scene numbers, or mark good takes you’ll want to use to put the final video together. Video EditingĪutomated editing tools make a ton of sense when you don’t have an operator behind a camera. It’s targeted at sports, but could work in a variety of settings. For instance, any time you need b-roll footage, this could potentially be an excellent solution. Then, the camera will automatically focus on the bearer, and keep them in the frame.Īlthough there is clearly a bit of a lag when keeping the subject in the frame, this technology will only improve over time. Their fully automated camera solution requires the subject to have a small device on their person. That’s very close to what SoloShot has done. It’s a logical next step to enable tripods to swivel to follow the action, gestures, or oral commands. Autofocus, face recognition, voice control, and other related technologies have been around for years. This type of technology could easily bleed over into other types of cameras.
Some of the most advanced features include the ability to react to gestures, recognize and actively track and film subjects, and to select the best route when returning to the home base. You almost don’t need a pilot to operate it. It uses multi-directional sensors to avoid obstacles, and offers different flight modes with varying levels of automation.
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Perhaps the most famous example of this is the DJI Phantom 4 Pro drone. Even more impressive, these drones can perform these feats while hovering perfectly still in the air and avoiding obstacles in flight without specific human direction to do so. The latest models can automatically follow a subject, and keep them perfectly centered in the frame as though a human were at the controls. Some of the biggest advancements have come from drones.
From filming and editing videos, to selecting and sharing clips online, AI is poised to change video production as we know it. When it comes to video, AI is beginning to impact many aspects of the production and distribution process. This leads to an innate drive to push boundaries when it comes to AI. It becomes an expected function of the software. If a particular feat has been programmed and achieved, it’s seen as less intelligent. The tricky part about defining AI is that it has a strong bias towards novelty. In the broadest terms, artificial intelligence (AI) is defined as “the theory and development of computer systems able to perform tasks that normally require human intelligence.” It includes diverse fields, such as robotics, machine learning, and the development of autonomous vehicles. Here’s our take on what you need to know about artificial intelligence and video.Īrtificial intelligence is a blanket term that encompasses a rapidly growing field. It impacts everything from how videos are filmed, edited, and discovered online, to future job opportunities in the field.
In fact, the field of artificial intelligence is very expansive, and incorporates everything from algorithms to machine learning and yes, robotics.Īlthough exciting, the rise of artificial intelligence has important implications for business video. When you think of artificial intelligence, your mind jumps to fascinating subjects like supercomputing, robots, and self-driving cars.
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