UTCS AI Colloquia - Sanjeev J. Koppal, Researcher, Texas Instruments, "Lithographic Vision Sensors"

Contact Name: 
Karl Pichotta
Location: 
GDC 6.302
Date: 
Jan 31, 2014 11:00am - 12:00pm
Host: 
Kristen Grauman

Signup Schedule: http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi

Talk Audience: UTCS Faculty, Grads, Undergrads, Other Interested Parties

Host:  Kristen Grauman

Talk Abstract: Miniature computing platforms will influence fields such as geographic and environment sensing, search and rescue, industrial control and monitoring, energy and health. Computer vision algorithms can broaden this impact by allowing small devices to utilize the rich visual information of their surroundings. However, achieving computer vision on small form factor devices is a challenge due to the severe constraints of power and mass.

Lithographic vision sensors are a class of devices that allow computer vision in these scenarios by leveraging two characteristics. First, every part of the sensor is jointly designed with the computer vision task in mind, in order to extract the maximum energy efficiency. Second, the optics of the system perform a significant portion of the computational burden. Balancing the performance of any particular computer vision algorithm with the physical aspects of a lithographic vision sensor (such as field-of-view, mass, power consumption etc) provides a rich source of interesting, new research problems.

Recent advances in material science and small-scale fabrication coupled with the rapid prototyping revolution have significantly increased the ease of designing, building, testing and iterating these devices. A key target of this research is to create a dictionary of low-power vision sensors for different task specific situations, analogous to how biological eyes are well suited for particular conditions. The broader goal is to build a general optimization and design framework that can produce these task-specific designs given certain physical constraints. In that sense, the ultimate goal is to build a "compiler" for visual sensors.

Speaker Bio: Sanjeev J. Koppal obtained his Masters and Ph.D. degrees from the Robotics Institute at Carnegie Mellon University, where his adviser was Prof. Srinivasa Narasimhan. After CMU, he was a post-doctoral research associate in the School of Engineering and Applied Sciences at Harvard University, with Prof. Todd Zickler. He received his B.S. degree from the University of Southern California in 2003. His interests span computer vision and computational photography and include novel cameras and micro sensors, digital cinematography, 3D cinema, image-based/light-field rendering, appearance modeling, 3D reconstruction, physics-based vision and active illumination. He is currently a researcher at Texas Instruments Imaging R&D. In the Spring of 2014 he will be joining the University of Florida's ECE department as an assistant professor.

Tags: