Bus passenger flow statistics algorithm based on deep learning

Yong Zhang, Wentao Tu, Kairui Chen, C. H. Wu, Li Li, W. H. Ip, C. Y. Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


Bus passenger flow statistics can be used to improve passenger travelling experience and reduce trip delay, this is very important for intelligent transportation. In this paper, a bus passenger flow statistics algorithm based on SSD (Single Shot MultiBox Detector) and Kalman filter is proposed to obtain passenger flow statistics from surveillance cameras on the buses. The method modifies the SSD model to a two-class model and trains the two-class SSD model using the bus dataset first, then the model is used to detect the position of the passengers in each frame and are tracked with the Kalman filter. Finally, according to the passenger trajectory, the traffic statistics of passenger getting on and off will be generated. The results of some conducted experiments show that the proposed bus passenger flow statistics algorithm is more accurate and robust than traditional methods.

Original languageEnglish
Pages (from-to)28785-28806
Number of pages22
JournalMultimedia Tools and Applications
Issue number39-40
Publication statusPublished - 1 Oct 2020


  • Bus passenger flow statistics
  • Computer vision
  • Deep learning
  • SSD algorithm

ASJC Scopus subject areas

  • Software
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


Dive into the research topics of 'Bus passenger flow statistics algorithm based on deep learning'. Together they form a unique fingerprint.

Cite this