A-CCNN: Adaptive CCNN for Density Estimation and Crowd Counting

Saeed Amirgholipour, Xiangjian He, Wenjing Jia, Dadong Wang, Michelle Zeibots

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

7 Citations (Scopus)

Abstract

Crowd counting, for estimating the number of people in a crowd using vision-based computer techniques, has attracted much interest in the research community. Although many attempts have been reported, real-world problems, such as huge variation in subjects' sizes in images and serious occlusion among people, make it still a challenging problem. In this paper, we propose an Adaptive Counting Convolutional Neural Network (A-CCNN) and consider the scale variation of objects in a frame adaptively so as to improve the accuracy of counting. Our method takes advantages of contextual information to provide more accurate and adaptive density maps and crowd counting in a scene. Extensively experimental evaluation is conducted using different benchmark datasets for object-counting and shows that the proposed approach is effective and outperforms state-of-the-art approaches.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
PublisherIEEE Computer Society
Pages948-952
Number of pages5
ISBN (Electronic)9781479970612
DOIs
Publication statusPublished - 29 Aug 2018
Externally publishedYes
Event25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
Duration: 7 Oct 201810 Oct 2018

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference25th IEEE International Conference on Image Processing, ICIP 2018
Country/TerritoryGreece
CityAthens
Period7/10/1810/10/18

Keywords

  • Adaptive Counting CNN
  • Crowd counting
  • Scale Variation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint

Dive into the research topics of 'A-CCNN: Adaptive CCNN for Density Estimation and Crowd Counting'. Together they form a unique fingerprint.

Cite this