Umesh Rajashekar's Research

Umesh's Research

"Results! Why, man, I have gotten a lot of results. I know several thousand things that won't work."

Classification Images at Eye Fixations
People: Prof. Al Bovik & Prof. Larry Cormack

The goal of this project was to investigate whether observers used structural cues to deploy their fixations as they searched for simple geometric targets embedded at very low signal-to-noise ratios in 1/f noise. By computing classification images at observers' fixations, we were able to reveal idiosyncratic, target-dependent features used by observers in this visual search task.

Relevant Publications:

U. Rajashekar, A. C. Bovik, and L. K. Cormack, "Visual Search in Noise: Revealing the Influence of Structural Cues by Gaze-contingent Classification Image Analysis", Journal of Vision, Special Issue on Finding visual features: Using stochastic stimuli, Vol: 6 No: 4, March 2006. Page(s): 379-386

SIVA: The Signal, Image, & Video AudioVisualizations
People: George Panayi, Frank Baumgartner, & Prof. Al Bovik

SIVA - The Signal, Image and Video Audiovisual Demonstration Gallery is a collection of didactic tools that facilitate a gentle introduction to concepts in signal and image processing. Equipped with informative visualizations and a user-friendly interface, SIVA uses novel LabVIEW and MATLAB based demonstrations to illustrate the power and beauty of signal and image processing algorithms. The SIVA demonstration gallery is being used at 350+ academic, industrial and other sites around the world.

Relevant Publications:

U. Rajashekar, G. C. Panayi, F. P. Baumgartner, and A. C. Bovik, "The SIVA Demonstration Gallery for Signal, Image, and Video Processing Education", IEEE Transactions On Education, Vol: 45 No: 4, November 2002, Page(s): 323-335

Real-time Foveation: An eye tracker-driven imaging system
People: Prof. Zhou Wang & Prof. Al Bovik

In the Fall of 2001, we built a real-time foveation filtering system to demonstrate the foveation feature of the HVS. The system records observers' gaze direction and automatically 'foveates' the image or video being observed in real time. Since the image/video at the point of gaze is always high-resolution, the foveated display is perceptually indistinguishable from the original to the observer!