An algorithm for recognising walkers

H. M. Lakany, G. M. Hayes

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

5 Citations (Scopus)


In this paper, we present an algorithm to recognise walking people, based upon extracting the spatio-temporal trajectories of the joints of a walking subject.

Subjects are filmed with LEDs attached to their joints and head such that the lights are the only objects visible in the film sequence — a method known as moving light displays (MLDs). Lights are tracked through the sequence of frames and are labelled based on human walking behaviour. In the case of self-occluded lights, a radial basis function neural network was trained and used for predicting the positions of occluded markers. The trajectory of each MLD is transformed using a 2D fast Fourier transform. Components of the FFT for all MLDs are considered as the feature vector of each subject. This is fed to a multi-layer perceptron (MLP) for classification.

The algorithm was used to recognise four subjects — 3 males and 1 female. For each subject, 10 gait cycles were used for training and 5 for testing the MLP. Backpropagation was used to train the network. Results show that the algorithm is a promising technique for recognising subjects by their gait.
Original languageEnglish
Title of host publicationInternational Conference on Audio- and Video-Based Biometric Person Authentication
Subtitle of host publicationFirst International Conference, AVBPA '97, Crans-Montana, Switzerland, March 12 - 14, 1997, Proceedings
Number of pages8
ISBN (Electronic)978-3-540-68425-1
ISBN (Print)978-3-540-62660-2
Publication statusPublished - 1997

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


  • spatio-temporal trajectories
  • walking
  • gait cycles
  • gait recognition

Cite this