Simultaneous license plate recognition and face detection application at the edge

Fikret Alim; Enes Kavakli; Sefa Burak Okcu; Ertugrul Dogan; Cevahir Cigla

doi:10.1117/12.2649988

15 March 2023 Simultaneous license plate recognition and face detection application at the edge

Fikret Alim, Enes Kavakli, Sefa Burak Okcu, Ertugrul Dogan, Cevahir Cigla

Proceedings Volume 12438, AI and Optical Data Sciences IV; 124380T (2023) https://doi.org/10.1117/12.2649988
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

Face recognition (FR) and license plate recognition (LPR) are very crucial algorithms for identification of humans and vehicles in several applications such as surveillance, traffic and access-control. The advances in small single-board computers with high parallel processing power capabilities and the use of low-power Neural Processing Units (NPU) inside embedded System on Chips (SoC), enable real-time face detection (FD) and LPR at the edge. On the other hand, it is still a challenge to run multiple algorithms concurrently with high accuracy and prompt execution (high frame rates) that requires a very efficient software/video analytics algorithm development. Both FR and LPR algorithms need two-stage processing that involve detection and recognition. In this study, we propose a method that enables simultaneous face detection associated with landmark and quality information and LPR at the edge. The FD pipeline detects and tracks the faces, extracts landmarks and quality of faces, to select appropriate faces for recognition and then sends them to face recognition server. LPR algorithm consecutively performs detection and recognition on the embedded platform. Extended YOLO model is utilized for face selection while pruned YOLO and LPRNet models are exploited for license plate detection and license plate reading, respectively. In order to enable real-time performance with high accuracy; optimized AI-models and software architecture are used. As a result of this study, we obtain a high-performance, high-precision and real-time combined face/LPR recognition system which can be very useful for surveillance and security applications.

Conference Presentation

Citation Download Citation

Fikret Alim, Enes Kavakli, Sefa Burak Okcu, Ertugrul Dogan, and Cevahir Cigla "Simultaneous license plate recognition and face detection application at the edge", Proc. SPIE 12438, AI and Optical Data Sciences IV, 124380T (15 March 2023); https://doi.org/10.1117/12.2649988

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