Low Level Signal Processing with Event-Based Sensor

Speaker

Keigo Hirakawa
Professor, Department of Electrical and Computer Engineering, University of Dayton.

Title

"Low Level Signal Processing with Event-Based Sensor"

Abstract

Event-Based Sensor (EBS) is a new type of image sensor whose pixels report changes in the irradiance asynchronously. Thanks to its sparse high data rate (10G events per second), low power (< 150mW), dynamic range (> 120dB), and high temporal resolution (microseconds accuracy), EBS has shown promising results in a number of novel applications to high speed imaging.  Working with asynchronous pixel data requires a new set of signal and image processing techniques, however, which we address in this presentation.  

After introduction about the sensor technology, we will showcase a number of our recent research progresses in EBS-based signal processing, including optical flow, event denoising, object detection, object tracking, pose estimation, intensity reconstruction, stereo matching, wavefront sensing, particle velocimetry, visual microphone, and passive ranging.

About Speaker

Keigo Hirakawa is a Professor, the Bernhard Schmidt Endowed Chair, and the Undergraduate Program Director of Electrical and Computer Engineering at the University of Dayton. Prior to joining UD in 2010, he was with Harvard University as a Research Associate of the Department of Statistics and School of Engineering and Applied Sciences. He has a BS in Electrical Engineering from Princeton University, MS and PhD in Electrical and Computer Engineering from Cornell University, and M.M. in Jazz Performance from New England Conservatory of Music.  

Prof. Hirakawa's research focuses on computational imaging, image processing, computer vision, and sensors. He is best known for his expertise in digital camera designs, and his contributions span color science, estimation theory, and statistical modeling.