Method for Gait Recognition Based on Multi-level Hierarchical Fusion Network
LI Zhe
LIU Yong
LIU Zhonghua
OU Weihua
Abstract：Gait recognition is a biometric technology that identifies individuals through their unique walking patterns.It is suitable for unconstrained environments and has broad application prospects.Although current methods focus on using body part based representations,they often overlook the hierarchical dependencies among local motion patterns.In this paper,we propose a multi-level hierarchical fusion model for extracting gait features from coarse to fine.Our framework integrates two strategies:multi-level hierarchical feature extraction and non-uniform hierarchical feature extraction.This enables fine-grained extraction of local features while emphasizing the interrelationships among local features.Verified by numerous experiments on widely recognized datasets,the method we proposed has been proven to be effective.While improving the model accuracy,this method also successfully maintains a reasonable balance in model complexity.
Keywords：local featuresmulti-level hierarchynon-uniformfeature fusiongait recognition
Publication Date：2025-04-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 42-47,94 )