Abstract: The advent (and commoditization) of low-cost 3D cameras is revolutionizing many application domains, including robotics, autonomous navigation, human computer interfaces, and recently even consumer devices such as cell-phones. Most modern 3D cameras (e.g., LiDAR) are active; they consist of a light source that emits coded light into the scene, i.e., its intensity is modulated over space, and/or time. The performance of these cameras is determined by their illumination coding functions.

I will talk about our work on developing a coding theory of active 3D cameras. This theory, for the first time, abstracts several seemingly different 3D camera designs into a common, geometrically intuitive space. Based on this theory, we design novel 3D cameras that achieve up to an order of magnitude higher performance as compared to the current state-of-the art. I will also briefly talk about our work toward developing `All-Weather’ 3D cameras that can operate in extreme real-world conditions, including outdoors (e.g., a robot navigating outdoors in bright sunlight and poor weather), under multi-camera interference (e.g., multiple robots navigating in a shared space such as a warehouse), and handle optically challenging objects such as shiny metal (e.g., for an industrial robot sorting machine parts).

Bio: Mohit Gupta is an Assistant Professor of Computer Sciences at the University of Wisconsin-Madison. He received B. Tech in Computer Science from IIT-Delhi, Ph.D. from the Robotics Institute, Carnegie Mellon University, and was a postdoctoral research scientist at Columbia University. He directs the WISION Lab with research interests broadly in computer vision and computational imaging. He has received best paper honorable mention awards at computer vision and photography conferences in 2014 and 2019, and a Sony Faculty Innovation Award in 2019. His research is supported by NSF, ONR, DARPA, Sony, Intel and Wisconsin Alumni Research Foundation.