International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | To Design an Automotive User Identification Using Multimodal Face Gait Fusion Techniques |
|---|---|
| ABSTRACT | This project, titled “Automotive User Identification Using Multimodal Face–Gait Fusion Techniques,” presents a robust biometric authentication system designed to enhance vehicle security and personalization. The proposed system integrates both facial recognition and gait analysis to accurately identify authorized users, overcoming limitations of unimodal biometric systems. A camera-based setup captures facial features and walking patterns, which are processed using computer vision and deep learning techniques. Feature-level fusion is employed to combine face and gait data, improving recognition accuracy under varying environmental conditions such as low lighting or partial occlusion. The system is implemented using a modular architecture, enabling real-time identification and seamless integration with automotive access control systems. Experimental results demonstrate improved reliability, accuracy, and resistance to spoofing compared to traditional single-modal approaches. This solution offers a scalable and efficient method for next-generation intelligent vehicle systems, ensuring enhanced security, user convenience, and adaptive personalization within modern automotive environments. |
| AUTHOR | A.R.ASHOK KUMAR, D GANDIMATHI, TAMIL SELVAM M, SANTHOSH S, CHERAN R Assistant Professor, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India UG Scholar, Department of Computer Science and Engineering, P.S.V College of Engineering and Technology, Mittapalli, Krishnagiri, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404086 |
| pdf/86_To Design an Automotive User Identification Using Multimodal Face Gait Fusion Techniques.pdf | |
| KEYWORDS | |
| References | 1. C. Fan, Y. Peng, and S. Yu, “GaitPart: Temporal Part-Based Model for Gait Recognition,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14225–14233, 2020. 2. R. Rao and P. Kumar, “Driver Identification and Vehicle Personalization using Face Recognition,” International Journal of Intelligent Systems, vol. 36, no. 5, pp. 2345–2356, 2021. 3. C. Fan, Z. Wang, and S. Yu, “OpenGait: Revisiting Gait Recognition Towards Better Practicality,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14700–14709, 2023. 4. S. Zou, H. Li, and J. Zhang, “Multi-Stage Adaptive Feature Fusion Neural Network for Multimodal Biometric Recognition,” IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 6, no. 1, pp. 45–58, 2024. 5. J. Wang, X. Ren, and L. Zhao, “Lightweight Multimodal Biometric Recognition Network for Real-Time Applications,” IEEE International Joint Conference on Biometrics (IJCB), pp. 1–8, 2025. |
