CRII: RI: Computational Thermal Imaging

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Imagine a future where autonomous vehicles can see through thick fog or even around corners. How many accidents could be avoided, how many lives could be saved, with this form of superhuman sensing? Today, ordinary computer vision systems do not generalize to bad weather or non-line-of-sight obstacle avoidance. This is because ordinary computer vision systems rely on visible light cameras that see colors that our eyes see. To overcome this roadblock, the investigative team will study computational thermal imaging, where novel end-to-end systems are designed with infrared optics and vision algorithms. These topics are usually studied separately. This research program will be integrated into a sequence of newly designed courses in computer vision and computational imaging at the University of California, Los Angeles.This project brings computational imaging to the realm of long-wave infrared wavelengths and studies the unique performance tradeoffs thereof. The research rests upon three pillars. In the first pillar, the investigative team will construct a 3D camera prototype that projects custom-designed structured light patterns at long-wave infrared wavelengths (circa 10 micrometer wavelengths of light). The structured light patterns may be specialized to the unique characteristics of long-wave infrared wavelengths. In the second pillar, the investigative team will probe deeper into the possibility of non-line-of-sight cameras that operate at long-wave infrared wavelengths. Creating a camera that can see around corners sounds like a daunting challenge, but the investigative team aims to exploit the specularity of reflections that are unique to long-wave infrared wavelengths. Finally, the investigative team will study the foundational differences between how scientists mathematically represent image data at long-wave infrared wavelengths as compared to visible light wavelengths.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.