华南农业大学学报2024，Vol.45Issue(5)：793-801,9.DOI:10.7671/j.issn.1001-411X.202403020
基于跨模态共享特征学习的夜间牛脸识别方法
Nighttime cattle face recognition based on cross-modal shared feature learning
摘要
Abstract
[Objective]To address the challenge of effectively recognizing cattle identity in the nighttime,and lay the technical foundation for 24-hour monitoring of cattle.[Method]A nighttime cattle face recognition method based on cross-modal shared feature learning was proposed.The model framework adopted a shallow dual-stream structure to effectively extract shared feature information from different modalities of cattle face images.Additionally,a triplet attention mechanism was introduced to capture intermodal interaction information across dimensions,enhancing the extraction of cattle identity information.Finally,an embedded extension module was utilized to further explore the representation of cross-modal identity information.[Result]The nighttime cattle face recognition model proposed in this article achieved a mean average precision,the first order cumulative matching eigenvalue(CMC-1)and the fifth order cumulative matching eigenvalue(CMC-5)of 90.68%,94.73%and 97.82%on the test set,respectively.Compared to the model without cross-modality training,the three indexes improved by 19.67,18.91 and 12.00 percentage points,respectively.[Conclusion]The proposed method provides a reliable solution for nighttime cattle identity recognition,laying a solid technical foundation for the application of continuous 24-hour monitoring of cattle.关键词
牛/身份识别/异质面部识别/跨模态/注意力机制/共享特征/夜间Key words
Cattle/Identification/Heterogeneous face recognition/Cross-modality/Attention mechanism/Shared feature/Nighttime分类
信息技术与安全科学引用本文复制引用
许兴时,王云飞,邓红兴,宋怀波..基于跨模态共享特征学习的夜间牛脸识别方法[J].华南农业大学学报,2024,45(5):793-801,9.基金项目
国家重点研发计划(2023YFD1301800) （2023YFD1301800）
国家自然科学基金(32272931) （32272931）
陕西省农业重点核心技术项目(2023NYGG005) （2023NYGG005）
陕西省科技创新引导计划(2022QFY11-02) （2022QFY11-02）
