MI3: Multi-intensity infrared illumination video database

Chia Hsin Chan, Hua Tsung Chen, Wen Chih Teng, Chin Wei Liu, Jen-Hui Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


Vision-based video surveillance systems have gained increasing popularity. However, their functionality is substantially limited under nighttime conditions due to the poor visibility caused by improper illumination. Equipped on night vision cameras, ordinary infrared (IR) illuminators of fixed-intensity usually lead to the imaging problem of overexposure (or underexposure) when the object is too close to (or too far from) the camera. To overcome this limitation, we use a novel multi-intensity IR illuminator to extend the effective range of distance of camera surveillance, and establish in this paper the MI3 (Multi-Intensity Infrared Illumination) database based on such an illuminator. The database contains intensity varying video sequences of several indoor and outdoor scenes. Ground truths including people counting and foreground labelling are provided for different research usages. Performances of related algorithms are tested for demonstration and evaluation.

Original languageEnglish
Title of host publication2015 Visual Communications and Image Processing, VCIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467373142
StatePublished - 1 Jan 2015
EventVisual Communications and Image Processing, VCIP 2015 - Singapore, Singapore
Duration: 13 Dec 201516 Dec 2015

Publication series

Name2015 Visual Communications and Image Processing, VCIP 2015


ConferenceVisual Communications and Image Processing, VCIP 2015


  • database
  • foreground identification
  • human detection
  • infrared
  • nighttime surveillance
  • people counting


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