ILGaCo: Incremental learning of gait covariate factors

Mu，Zihao1; Castro，Francisco M.2; Marin-Jimenez，Manuel J.3; Guil，Nicolas2; Li，Yan Ran1,4; Yu，Shiqi5

10.1109/IJCB48548.2020.9304857

2020-09-28

IJCB 2020 - IEEE/IAPR International Joint Conference on Biometrics

Gait is a popular biometric pattern used for identifying people based on their way of walking. Traditionally, gait recognition approaches based on deep learning are trained using the whole training dataset. In fact, if new data (classes, view-points, walking conditions, etc.) need to be included, it is necessary to re-train again the model with old and new data samples. In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset. Instead, our approach performs a shorter training process with the new data and a small subset of previous samples. This way, our model learns new information while retaining previous knowledge. We evaluate iLGaCo on CASIA-B dataset in two incremental ways: adding new view-points and adding new walking conditions. In both cases, our results are close to the classical 'training-from-scratch' approach, obtaining a marginal drop in accuracy ranging from 0.2% to 1.2%, what shows the efficacy of our approach. In addition, the comparison of iLGaCo with other incremental learning methods, such as LwF and iCarl, shows a significant improvement in accuracy, between 6% and 15% depending on the experiment.

其他

英语

EI

20210409828150

Biometrics ; Deep learning ; Gait analysis

Bioengineering and Biology:461 ; Biomechanics, Bionics and Biomimetics:461.3

2-s2.0-85099677815

Scopus

1.College of Computer Science and Software Engineering,Shenzhen University,China
2.University of Málaga,Department of Computer Architecture,Spain
3.University of Córdoba,Department of Computing and Numerical Analysis,Spain
4.Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS),China
5.Southern University of Science and Technology,Department of Computer Science and Engineering,China

Mu，Zihao,Castro，Francisco M.,Marin-Jimenez，Manuel J.,et al. ILGaCo: Incremental learning of gait covariate factors[C],2020.