Visual recognition to access and analyze people density and flow patterns in indoor environments

C. Ruz, C. Pieringer, B. Peralta, I. Lillo, P. Espinace, R. Gonzalez, B. Wendt, D. Mery, A. Soto

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

2 Citations (Scopus)

Abstract

This work describes our experience developing a system to access density and flow of people in large indoor spaces using a network of RGB cameras. The proposed system is based on a set of overlapped and calibrated cameras. This facilitates the use of geometric constraints that help to reduce visual ambiguities. These constraints are combined with classifiers based on visual appearance to produce an efficient and robust method to detect and track humans. In this work, we argue that flow and density of people are low level measurements that need to be complemented with suitable analytic tools to bridge semantic gaps and become useful information for a target application. Consequently, we also propose a set of analytic tools that help a human user to effectively take advantage of the measurements provided by the system. Finally, we report results that demonstrate the relevance of the proposed ideas.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781479966820
DOIs
Publication statusPublished - 1 Jan 2015
Event2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015 - Waikoloa, United States
Duration: 5 Jan 20159 Jan 2015

Conference

Conference2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015
Country/TerritoryUnited States
CityWaikoloa
Period5/01/159/01/15

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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