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Home Machine Learning

New “3D Semantic Camera” Promises Breakthrough Capabilities

September 20, 2019
in Machine Learning
New “3D Semantic Camera” Promises Breakthrough Capabilities
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Hyperspectral imaging (or imaging spectroscopy) involves collecting and processing many bands of light intensity data from across the spectrum, rather than just the Red/Green/Blue bands that make up visible light. Because chemical bonds absorb light at specific wavelengths, bouncing certain kinds of light off a material and measuring the reflectance curve allows the imaging of the unique spectral signature of that material. This in turn enables the accurate identification of the specific materials in each pixel of a visible scene, even at long ranges. 

Spectroscopy is a critical tool in modern science, and hyperspectral imaging has been used for some time for defense applications including spy satellites and surveillance as well as for oil and gas exploration, mineralogy, astronomy and agriculture. During a phone interview with The Drive, Outsight co-founder and CEO Cedric Hutchings was cagey about the details of this first application of active hyperspectral imaging but said that the development of a low-power, eye-safe “broadband laser” was critical to Outsight’s solution. Though equally cagey on costs, Hutchings said that Outsight would be targeting ADAS applications as well as fully-autonomous vehicles, meaning the cost could reach a point where it could be sold profitably as an option on a consumer car. 

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The result is a sensor with remarkable capabilities that seem to fill an important gap in the modern automated driving sensor suite. I’ve written about the potential value of thermal imaging sensors as a tool for the challenging task of identifying and tracking “vulnerable road users” (pedestrians and cyclists) in the wake of the fatal Tempe, AZ crash of an Uber self-driving test vehicle into a pedestrian, and the ability to quickly and precisely classify materials using the 3D Semantic Camera seems like another useful tool to wield against this thorny challenge. Beyond that, the ability to do things like identify things like black ice on a road surface, which can be extremely difficult using cameras (and basically impossible using radar/lidar) has obvious potential both for AVs but also for ADAS and “augmented driving” systems.

Credit: Google News

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