Gait-based Intelligence, Surveillance, Reconnaissance (ISR) System
Published:
🔔 This project is for 2023 National College Student Information Security Contest, which will be held on 17-21 August, 2023, so detail cannot be publish now.
Background
The rapid development of digitalization in the 21st century has brought about various information security challenges for citizens. Among these challenges, authentication security has received increasing attention. The traditional authentication methods such as passwords, fingerprints, faces and irises have some limitations and security risks. To improve the accuracy and security of authentication, researchers have explored other biometric recognition techniques for authentication, among which gait recognition as a novel biometric recognition technique has attracted widespread attention.
Gait recognition is an authentication method based on human dynamic walking characteristics. Human gait is determined by the coordination of skeleton, muscle and joint, which has uniqueness, stability and difficulty in forgery. Compared with traditional biometric features, human gait has the advantages of long distance, non-intrusive and difficult to disguise. With the rapid progress of computer vision, pattern recognition and machine learning technologies, gait recognition has made great strides. Modern gait recognition techniques use deep learning methods to learn and extract high-level feature representations from large-scale data.
The gait recognition method based on deep learning has a wide application potential in the field of identity authentication. Its accuracy and robustness make it suitable for security access control, border security and linkage Skynet and other fields, providing individuals with high credibility identity authentication services. In addition, the gait recognition technology based on deep learning can also be combined with other biometric recognition methods such as face recognition, fingerprint recognition and so on to build a multimodal identity authentication system, which further improves the accuracy and reliability of authentication.
