RT Conference Proceedings
T1 Evaluation of CNN architectures for gait recognition based on optical flow maps
A1 Castro, Francisco M.
A1 Marín-Jiménez, Manuel J.
A1 Guil-Mata, Nicolás
A1 López-Tapia, S.
A1 Pérez de la Blanca, N.
K1 Identificación
AB This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.
YR 2017
FD 2017
LK http://hdl.handle.net/10630/14592
UL http://hdl.handle.net/10630/14592
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026