Silhouette-based gait recognition via deterministic learning
作者：
Highlights：
• We present a silhouette-based gait recognition method via deterministic learning.
• The dynamics of gait motions can be learned by using RBF neural networks.
• The test gait pattern can be recognized according to the smallest error principle.
• The discriminability provided by the dynamics of the silhouette features is strong.
• We show good recognition performance on four widely used gait databases.
摘要
Highlights•We present a silhouette-based gait recognition method via deterministic learning.•The dynamics of gait motions can be learned by using RBF neural networks.•The test gait pattern can be recognized according to the smallest error principle.•The discriminability provided by the dynamics of the silhouette features is strong.•We show good recognition performance on four widely used gait databases.
论文关键词：Gait recognition,Deterministic learning,Silhouette features,Gait dynamics,Smallest error principle
论文评审过程：Received 18 April 2013, Revised 15 February 2014, Accepted 13 April 2014, Available online 28 April 2014.
论文官网地址：https://doi.org/10.1016/j.patcog.2014.04.014
