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IRIS: Integrated Retinal Functionality in Image Sensors.

Zihan Yin1, Md Abdullah-Al Kaiser1, Lamine Ousmane Camara2

  • 1Information Sciences Institute, University of Southern California, Los Angeles, CA, United States.

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|September 18, 2023
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Summary
This summary is machine-generated.

This study introduces novel neuromorphic image sensors inspired by the retina. These sensors implement advanced motion detection for real-time decision-making in dynamic environments.

Keywords:
Looming Detectioncircuit designimage sensorneuromorphic sensorobject motion sensitivityretina inspired sensor

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Area of Science:

  • Neuroscience
  • Computer Engineering
  • Electrical Engineering

Background:

  • Neuromorphic image sensors mimic the biological retina for visual computation.
  • Early sensors implemented basic retinal functions; advanced downstream processing remains largely unexplored.
  • Recent discoveries in retinal circuits offer new opportunities for sensor development.

Purpose of the Study:

  • To develop a technology-circuit co-design for implementing advanced motion computations in neuromorphic image sensors.
  • To integrate object motion sensitivity and looming detection at the sensor's output stage.
  • To enable real-time, energy-efficient decision-making for vision-based systems.

Main Methods:

  • Utilized a technology-circuit co-design approach.
  • Simulated proposed circuits on Globalfoundries 22 nm technology node.
  • Leveraged advances in semiconductor chip stacking technology.

Main Results:

  • Demonstrated the feasibility of implementing object motion sensitivity and looming detection.
  • Validated that the retina-inspired circuits can be fabricated on existing image sensing platforms.
  • Showcased the potential for integration using advanced chip stacking.

Conclusions:

  • The proposed Integrated Retinal Functionality in Image Sensors (IRIS) technology enables advanced motion processing.
  • IRIS technology can be fabricated using current semiconductor manufacturing capabilities.
  • This advancement promises to enhance machine vision applications requiring low-bandwidth, real-time decision-making.