Clips is a small camera with a special superpower: it understands enough about what it sees that it can take pictures for you. One notable example is the recently launched Google Clips camera. YOLO Real-Time Object Detection in actionĬameras enabled with machine learning therefore have the potential to both automate existing functions of the camera as a tool for human use and extend its creative possibilities far beyond image capture. It's not just that computers see like people, it's that computers can see like computers, and that makes all sorts of things possible." In media analyst and venture capitalist Benedict Evans' recent Ten Year Futures presentation, he discussed the potential impact of machine learning on cameras in the near future: "You turn the image sensor into a universal input for a computer. In the years since, machine learning has advanced by leaps and bounds in both accuracy and speed-see, for instance, the more recent open-source YOLO Real-Time Object Detection technique for comparison-with the potential to transform how we interface with cameras and computers alike. Timo Arnall explored this emerging capability of machines to interpret images in Robot Readable World, a collection of computer vision videos from 2012.
#The noun project jobs software
Software trained on vast datasets of labeled images can recognize things like vehicles, dogs, cats, and people, along with facial features, emotions, and second-order information like movement vectors and gaze direction from raw images and videos. Perhaps the most impactful influence on the camera is being brought about by computer vision: empowering cameras to not only capture various kinds of images but to also parse visual information-effectively, to understand the world. New capabilities in software, new hardware formats and imaging technologies, and emerging user behaviors around image creation are radically reshaping the object we know of as the "camera" into new categories. But the cameras we encounter every day bear little resemblance-in form or function-to this vestigial object.
0 kommentar(er)
