Ayush Jamdar (UCSD): “ISET-LFM: A Physics-based Simulation Framework and Dataset for LED Flicker in Automotive Imaging”

Speaker: Ayush Jamdar (UCSD)

Title: ISET-LFM: A Physics-based Simulation Framework and Dataset for LED Flicker in Automotive Imaging

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Abstract:  LED flicker is a persistent artifact in automotive imaging where lights modulated via Pulse Width Modulation (PWM) appear steady to humans but produce severe temporal intensity variations in captured video. These artifacts can lead to the misidentification of traffic signals, turn and brake signals, or emergency strobes in Advanced Driver Assistance Systems (ADAS), posing significant known safety risks. While hardware mitigations like split-pixel sensor architectures reduce flicker, they introduce a fundamental trade-off with motion blur. This work explores the development of ISET-LFM, an open-source physics-based simulation framework built upon the ISET ecosystem, specifically ISET3D and ISETCam, to model the entire imaging chain from 3D scene dynamics to detailed sensor electronics. We will discuss the integration of an analytical PWM flicker model with active camera transforms to simulate realistic non-uniform motion blur. The framework enables the generation of simultaneous dual-exposure radiance maps alongside guaranteed flicker-free ground truth, providing a critical resource for benchmarking and training learned LED flicker mitigation (LFM) algorithms.

Bio:  Ayush M. Jamdar recently earned his Master’s in Electrical and Computer Engineering from UC San Diego, where he specialized in signal and image processing. During a joint 2025 residency as a Camera Systems Intern at OmniVision and a Research Affiliate at Stanford’s VISTA Lab, Ayush developed ISET-LFM—an open-source framework designed to bridge the gap between simulation and real-world automotive sensor performance. Previously a member of the UCSD Computational Imaging Systems Lab and an alumnus of IIT Madras, his work sits at the intersection of computational imaging, physics-based simulation, and machine learning. Ayush is now joining Glass Imaging, a cutting-edge computational imaging startup in San Mateo, CA.