[Studies in Computational Intelligence 481] Artur Babiarz, Robert Bieda, Karol Jędrasiak, Aleksander Nawrat (auth.), Aleksander Nawrat, Zygmunt Kuś (eds.) - Vision Based Systemsfor UAV Applications (2013, Sprin

Feature Extraction and HMM-Based
Classification of Gait Video Sequences
for the Purpose of Human Identification
Henryk Josiński, Daniel Kostrzewa, Agnieszka Michalczuk, Adam Świtoński,
and Konrad Wojciechowski
Abstract. The authors present results of the research on human recognition based
on the video gait sequences from the CASIA Gait Database. Both linear (principal
component analysis; PCA) and non-linear (isometric features mapping; Isomap
and locally linear embedding; LLE) methods were applied in order to reduce data
dimensionality, whereas a concept of hidden Markov model (HMM) was used for
the purpose of data classification. The results of the conducted experiments
formed the main subject of analysis of classification accuracy expressed by means
of the Correct Classification Rate (CCR).
Keywords: dimensionality reduction, gait-based human identification, Hidden
Markov model, manifold learning.
1 Introduction
Gait is defined as coordinated, cyclic combination of movements which results in
human locomotion [1]. Gait is considered as one of behavioral biometric features.
A unique advantage of gait as a biometric is that it offers potential for recognition
at a distance or at low resolution or when other biometrics might not be
perceivable [2] especially from UAVs [26]. Gait can be captured by twodimensional
video cameras of surveillance systems or by much accurate motion
capture (mocap) systems which acquire motion data as a time sequence of poses.
Henryk Josiński ⋅ Daniel Kostrzewa ⋅ Agnieszka Michalczuk ⋅ Adam Świtoński ⋅
Konrad Wojciechowski
Silesian University of Technology, Institute of Computer Science,
Akademicka 16, 44-101 Gliwice, Poland
e-mail: {henryk.josinski,adam.switonski,agnieszka.michalczuk,
daniel.kostrzewa,konrad.wojciechowski}@polsl.pl
A. Nawrat and Z. Kuś (Eds.): Vision Based Systems for UAV Applications, SCI 481, pp. 233–245.
DOI: 10.1007/978-3-319-00369-6_15 © Springer International Publishing Switzerland 2013