计算机应用与软件2024，Vol.41Issue(1)：139-145,7.DOI:10.3969/j.issn.1000-386x.2024.01.021
基于多特征融合卷积的步态识别算法研究
GAIT RECOGNITION ALGORITHM BASED ON MULTI-FEATURE FUSION CONVOLUTION
摘要
Abstract
Aimed at the weak learning and classification ability of the backbone network in the GaitSet algorithm,the gait recognition algorithm based on the multi-feature fusion convolution(MFFC-GaitSet)is proposed.The algorithm reconstructed the GaitSet network by multi-feature fusion convolution to enhance the network learning ability,and smoothed and optimized the ternary loss function.The gait contour map was repaired by morphological processing.The algorithm was validated on the Casia-B dataset and achieved a gait recognition accuracy of 85.811％,with the increase of 2.6％.The model weight was increased by only 6％.The algorithm could effectively reduce the negative influence of complex environment on gait recognition and achieve high-precision gait recognition in complex environment.The experimental results show that the method can achieve more accurate gait recognition with better robustness and generalization ability.关键词
步态识别/多特征融合/形态学处理/三元组平滑优化/Casia-B数据集Key words
Gait recognition/Multi-feature fusion/Morphological processing/Triplet smoothing optimization/Casia-B dataset分类
信息技术与安全科学引用本文复制引用
杨鹏,应娜,李怡菲..基于多特征融合卷积的步态识别算法研究[J].计算机应用与软件,2024,41(1):139-145,7.基金项目
浙江省自然科学基金项目(LY16F010013). （LY16F010013）
