Idling Car Detection with ConvNets in Infrared Image Sequences

Muhammet Bastan, Kim Hui Yap, Lap Pui Chau

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

We propose a system to detect and localize idling cars in infrared (IR) image sequences for law enforcement to reduce vehicular emission. To this end, we leverage the differences in spatio-temporal heat signatures of idling and stopped cars and monitor car temperatures with a long-wavelength IR camera. We collected a dataset by recording IR image sequences of cars in car parks and trained a ConvNet-based car detector to localize stationary cars in the IR sequences, by utilizing transfer learning and models pre-trained on regular RGB/grayscale images. Then, we used ConvNets with a 3D stack of cropped frames as input to model the spatio-temporal evolution of car temperature over time and detect idling cars. We present promising experimental results on our IR image dataset.

Original languageEnglish
Title of host publication2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538648810
DOIs
Publication statusPublished - 26 Apr 2018
Externally publishedYes
Event2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Florence, Italy
Duration: 27 May 201830 May 2018

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2018-May
ISSN (Print)0271-4310

Conference

Conference2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Country/TerritoryItaly
CityFlorence
Period27/05/1830/05/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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