A systematic deep learning based overhead tracking and counting system using rgb-d remote cameras

Munkhjargal Gochoo, Syeda Amna Rizwan, Yazeed Yasin Ghadi, Ahmad Jalal, Kibum Kim

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Automatic head tracking and counting using depth imagery has various practical applications in security, logistics, queue management, space utilization and visitor counting. However, no currently available system can clearly distinguish between a human head and other objects in order to track and count people accurately. For this reason, we propose a novel system that can track people by monitoring their heads and shoulders in complex environments and also count the number of people entering and exiting the scene. Our system is split into six phases; at first, prepro-cessing is done by converting videos of a scene into frames and removing the background from the video frames. Second, heads are detected using Hough Circular Gradient Transform, and shoulders are detected by HOG based symmetry methods. Third, three robust features, namely, fused joint HOG-LBP, Energy based Point clouds and Fused intra-inter trajectories are extracted. Fourth, the Apriori-Association is implemented to select the best features. Fifth, deep learning is used for accu-rate people tracking. Finally, heads are counted using Cross-line judgment. The system was tested on three benchmark datasets: the PCDS dataset, the MICC people counting dataset and the GOTPD dataset and counting accuracy of 98.40%, 98%, and 99% respectively was achieved. Our system obtained remarkable results.

Original languageEnglish
Article number5503
JournalApplied Sciences (Switzerland)
Volume11
Issue number12
DOIs
Publication statusPublished - Jun 2 2021

Keywords

  • Apriori-Association
  • Cross-line judgment
  • Deep learning
  • Head tracking
  • Hough Circular Gradient Transform and Fused intra-inter trajectories

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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