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A Primer on Hybrid Event-Based Image Vision

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A Primer on Hybrid Event-Based Image Vision

Presented by: Daisuke Saito, OMNIVISION

Neuromorphic imaging, also known as event-based vision sensing (EVS), can generate high-temporal resolution data from a pixel-level event detection of relative illumination that exceeds a defined contrast threshold. This saves bandwidth and power for portions of the scene that remain static and dedicates it to where things are happening. Hence, EVS is a promising imaging technology to capture sparse, fast motion in a power-efficient manner. As EVS lacks an absolute reference, a significant number of use cases utilize a combination of conventional CMOS image sensors and EVS.

Saito presents a hybrid EVS and CMOS image sensor and highlight use cases. This technology can address the field of photography as well as machine vision. He further illustrates how to generate ground truth reference data for algorithm development, which is a key activity to accelerate the development of these new applications.


About the presenter
Daisuke SaitoDaisuke Saito received his bachelor’s and master’s degrees in applied physics from Tsukuba University, Tsukuba, Japan in 2005 and 2007, respectively. He was with Sony Corporation and Sony Semiconductor Solutions Corporation, Atsugi, Japan since 2007 as a device engineer and section chief in the research and development of a semiconductor device field. He studied at UC Berkeley and UC Davis, CA as a visiting scholar from 2013 to 2014 and he worked for imec from 2016 to 2020.

Saito contributed to the production of LED displays (CLEDIS), the device design, process integration, and characterization of “MEMS gyro sensors”, “optical MEMS devices”, and “In-memory computing”. He has worked for OMNIVISION, Santa Clara, CA, since 2022 where he is currently working as a system designer for image sensors in the office of CTO. Saito authored or co-authored more than 10 scientific papers and conferences, and he holds over 20 pending or issued patents.




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