Visual recognition of aircraft marshalling signals using gesture phase analysis

Cheolmin Choi, Jung Ho Ahn, Hyeran Byun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Visual gesture recognition is one of the main areas of research in human-computer and human-robot interfaces. In this paper we present a novel visual gesture recognition method for aircraft marshalling signals. To capture hand motion information, we used a color-based tracking algorithm with an adaptive window for each frame. A feature selection algorithm was used to classify the motion information into four different gesture phases. By using the gesture phase information, we built the gesture model, which consisted of a symbol sequence and a number of probabilities. Each gesture model was learned from the longest common subsequence (LCS) of a set of symbol sequences and the probability of the symbols. A similarity measure using the proposed gesture model is presented that combines the deterministic and probabilistic matching scores. In the experiments we show the efficiency and accuracy of the proposed method.

Original languageEnglish
Title of host publication2008 IEEE Intelligent Vehicles Symposium, IV
Number of pages6
Publication statusPublished - 2008
Event2008 IEEE Intelligent Vehicles Symposium, IV - Eindhoven, Netherlands
Duration: 2008 Jun 42008 Jun 6

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Other2008 IEEE Intelligent Vehicles Symposium, IV

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Automotive Engineering
  • Computer Science Applications


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