Interessantes Video über die Rolle von thermischer Bilderkennung beim autonomen Fahren. Spannend!
In an effort to advertise thermal imaging’s self-driving functionality, FLIR has developed its own visual awareness software and a new camera for demonstration purposes. The way it works is very straightforward. The camera is no larger than a GoPro, ideally planted somewhere on the top of the car, just behind the windshield in the middle of the width of the roof, which is where a lot of new cars placing cameras anyway. The application I witnessed was very simple, with a FLIR camera and a standard camera mounted side-by-side, connected to a relatively powerful gaming laptop via USB cables. In this application, some of the capabilities of the setup is limited by the computer hardware and the fact that we were using USB connections. On the demonstration screen inside the car, I saw a side-by-side view of what the standard camera was seeing, and a synced-up feed of what the thermal camera was seeing in black and white, in real time. Since it was dark outside, the thermal image was picking up a remarkable amount more data than the standard camera. While in our demo, the thermal feed was in black and white—black being cooler areas of the image with white being the warmest areas of the image, and hundreds of shades of gray in between—it can be programed to have temperature ranges register in various colors, like the average range of human body temperature, for example.Pedestrian figures stand out in the image as moving, glowing white human-shaped figures, with a clear outline that any person watching could instantly recognize, which is a good sign for any computer program trying to do the same. The way the computer analyzes the video feeds works with over 14,000 pre-programmed annotated visuals.
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