Runsheng Wang1, Hefei Ling1,*, Ping Li1, Yuxuan Shi1, Lei Wu1, Jialie Shen2
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3045-3060, 2021, DOI:10.32604/cmc.2021.017275
- 06 May 2021
Abstract Gait recognition is a biometric technique that captures human walking pattern using gait silhouettes as input and can be used for long-term recognition. Recently proposed video-based methods achieve high performance. However, gait covariates or walking conditions, i.e., bag carrying and clothing, make the recognition of intra-class gait samples hard. Advanced methods simply use triplet loss for metric learning, which does not take the gait covariates into account. For alleviating the adverse influence of gait covariates, we propose cross walking condition constraint to explicitly consider the gait covariates. Specifically, this approach designs center-based and pair-wise loss More >
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