AREST: Attention-Based Red-Light Violation Detection for Safety Technology

• Published in: 2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) pp. 1 - 7
• Main Authors: Kim, Harim, Kim, Minchae, Kim, Taewoo, Cho, Kyujin, Hong, Charmgil
• Format: Conference Proceeding
• Language: English
• Published: IEEE 15-07-2024
• Subjects: Encoding; Road safety; Sensors; Shared transport; Surveillance; Traffic control; Transformers
• ISSN: 2643-6213
• DOI: 10.1109/AVSS61716.2024.10672611

As car-sharing services evolve, there is a growing effort to analyze users' safe driving behaviors and effectively manage shared vehicles. Unlike previous researches that focus on simple situations like sudden acceleration and lane departure using cameras with additional sensors, we introduce a new approach that detects more complex traffic rule violation, especially red-light violation, using only the monocular dashcam videos. The proposed framework employs the attention mechanism of Transformer, and effectively encodes the traffic signal objects and contextual information within the video. It utilizes a novel method, POISE (Positional Object Information by Spatial Encoding), to handle the positional information of traffic signal objects. Our quantitative and qualitative evaluations demonstrate the effectiveness of our proposed framework in detecting red-light violations compared to existing methods.