The future of computational imaging

This podcast episode explores various fields and technologies such as computational imaging, HDR imaging, computational photography, indirect light transport, optical computing, generative AI, and virtual reality. It delves into applications ranging from autonomous cars to Hollywood production, addressing challenges, takeaways, and future potential. Takeaways • Computational imaging optimizes hardware and software components to capture better images, used in fields like autonomous cars, microscopy, and cell phone cameras. • HDR imaging combines multiple exposures to create images with wider dynamic range, improving both bright and dark area exposure. • Computational photography combines photography and computer science to create images beyond regular cameras' capabilities, allowing effects like depth maps and non-line of sight photography. • Indirect light transport involves using active illumination and mathematical inverse systems to reconstruct hidden objects. • Optical computing shows potential for power-efficient data pre-processing in systems like drones, reducing power consumption and latency. • Combining physics and generative AI enables realistic 3D content creation like digital humans, aiding Hollywood production with physics-based modeling. • Creating immersive virtual reality experiences faces challenges like display resolution, latency, accurate depth perception, and VR sickness, requiring new technologies and headset design improvements.