Gait recognition is an important biometric technique for video
surveillance tasks, due to the advantage of using it at distance. In
this paper, we present a persistent homology-based method to extract
topological features (the so-called topological gait signature) from the
the body silhouettes of a gait sequence. It has been used before in sev-
eral conference papers of the same authors for human identi cation,
gender classi cation, carried object detection and monitoring human
activities at distance. The novelty of this paper is the study of the sta-
bility of the topological gait signature under small perturbations and
the number of gait cycles contained in a gait sequence. In other words,
we show that the topological gait signature is robust to the presence
of noise in the body silhouettes and to the number of gait cycles con-
tained in a given gait sequence. We also show that computing our
topological gait signature of only the lowest fourth part of the body
silhouette, we avoid the upper body movements that are unrelated to
the natural dynamic of the gait, caused for example by carrying a bag
or wearing a coat.Ministerio de Economía y Competitividad MTM2015-67072-
