Improved Spatio-Temporal Convolutional Neural Networks for Traffic Police Gestures Recognition

Zhixuan Wu, Nan Ma*, Yiu Ming CHEUNG, Jiahong Li, Qin He, Yongqiang Yao, Guoping Zhang

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

In the era of artificial intelligence, human action recognition is a hot spot in the field of vision research, which makes the interaction between human and machine possible. Many intelligent applications benefit from human action recognition. Traditional traffic police gesture recognition methods often ignore the spatial and temporal information, so its timeliness in human computer interaction is limited. We propose a method that is Spatio-Temporal Convolutional Neural Networks (ST-CNN) which can detect and identify traffic police gestures. The method can identify traffic police gestures by using the correlation between spatial and temporal. Specifically, we use the convolutional neural network for feature extraction by taking into account both the spatial and temporal characteristics of the human actions. After the extraction of spatial and temporal features, the improved LSTM network can be used to effectively fuse, classify and recognize various features, so as to achieve the goal of human action recognition. We can make full use of the spatial and temporal information of the video and select effective features to reduce the computational load of the network. A large number of experiments on the Chinese traffic police gesture dataset show that our method is superior.

Original languageEnglish
Title of host publicationProceedings - 2020 16th International Conference on Computational Intelligence and Security, CIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages109-115
Number of pages7
ISBN (Electronic)9780738143118
DOIs
Publication statusPublished - Nov 2020
Event16th International Conference on Computational Intelligence and Security, CIS 2020 - Nanning, Guangxi, China
Duration: 27 Nov 202030 Nov 2020

Publication series

NameProceedings - 2020 16th International Conference on Computational Intelligence and Security, CIS 2020

Conference

Conference16th International Conference on Computational Intelligence and Security, CIS 2020
Country/TerritoryChina
CityNanning, Guangxi
Period27/11/2030/11/20

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Health Informatics

User-Defined Keywords

  • Artificial intelligence
  • Human action recognition
  • Improved LSTM network
  • Spatio-Temporal feature
  • Traffic police gesture

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