Counting People Based on Linear, Weighted, and Local Random Forests

Helia Farhood, Xiangjian He, Wenjing Jia, Michael Blumenstein, Hanhui Li

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

4 Citations (Scopus)

Abstract

Recently, many works have been published for counting people. However, when being applied to real-world train station videos, they have exposed many limitations due to problems such as low resolution, heavy occlusion, various density levels and perspective distortions. In this paper, following the recent trend of regression-based density estimation, we present a linear regression approach based on local Random Forests for counting either standing or moving people on station platforms. By dividing each frame into sub-windows and extracting features with ground truth densities as well as learned weights, we perform a linear transformation for counting people to overcome the perspective problems of the existing patch-based approaches. We present improvements against several recent baselines on the UCSD dataset and a dataset of CCTV videos taken from a train station. We also show improvements in speed compared with the state-of-the-art models based on detection and Deep Learning.

Original languageEnglish
Title of host publicationDICTA 2017 - 2017 International Conference on Digital Image Computing
Subtitle of host publicationTechniques and Applications
EditorsYi Guo, Manzur Murshed, Zhiyong Wang, David Dagan Feng, Hongdong Li, Weidong Tom Cai, Junbin Gao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
ISBN (Electronic)9781538628393
DOIs
Publication statusPublished - 19 Dec 2017
Externally publishedYes
Event2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017 - Sydney, Australia
Duration: 29 Nov 20171 Dec 2017

Publication series

NameDICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications
Volume2017-December

Conference

Conference2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017
Country/TerritoryAustralia
CitySydney
Period29/11/171/12/17

Keywords

  • crowd counting
  • Density estimation
  • linear regression
  • Random Forest

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing

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