A Time-Memory-based CMOS Vision Sensor with In-Pixel Temporal Derivative Computing for Multi-Mode Image Processing

  • Dong Woo Jee
  • , Seong Min Ko
  • , Kishore Kasichainula
  • , Injune Yeo
  • , Yu Cao
  • , Jae Sun Seo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents in-pixel and near-pixel processing circuit techniques for multi-mode processing CMOS vision sensor. The new design includes a checkerboard patch-based pixel circuit and column-shared frame difference processing circuits that detect a patch-level temporal change and generate lb event signal. In-pixel time memory circuit is proposed to process a temporal derivative of the event in both area and power efficient way. The 324× 252 vision sensor is implemented in 0.18 μ m CMOS process and consumes 4.79 μ W @12.5fps showing FoM of 42.2pJ/pix. frame in the patch mode operation for frame difference-based motion detection and temporal derivative generation.

Original languageEnglish (US)
Title of host publicationESSCIRC 2023 - IEEE 49th European Solid State Circuits Conference
PublisherIEEE Computer Society
Pages109-112
Number of pages4
ISBN (Electronic)9798350304206
DOIs
StatePublished - 2023
Event49th IEEE European Solid State Circuits Conference, ESSCIRC 2023 - Lisbon, Portugal
Duration: Sep 11 2023Sep 14 2023

Publication series

NameEuropean Solid-State Circuits Conference
Volume2023-September

Conference

Conference49th IEEE European Solid State Circuits Conference, ESSCIRC 2023
Country/TerritoryPortugal
CityLisbon
Period9/11/239/14/23

Keywords

  • frame difference
  • in-pixel processing
  • in-sensor computing
  • multi-mode image processing
  • nearpixel processing
  • temporal derivative
  • vision sensor

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A Time-Memory-based CMOS Vision Sensor with In-Pixel Temporal Derivative Computing for Multi-Mode Image Processing'. Together they form a unique fingerprint.

Cite this