2026-04-14T19:31:12Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/681012024-06-13T19:01:01Zcom_10324_1191com_10324_931com_10324_894col_10324_1379

Bartolomé Hornillos, César San José Revuelta, Luis Miguel Aguiar Pérez, Javier Manuel García Serrada, Carlos Vara Pazos, Eduardo Casaseca de la Higuera, Juan Pablo 2024 Producción Científica We present an automatic road incident detector characterised by a low computational complexity for easy implementation in affordable devices, automatic adaptability to changes in scenery and road conditions, and automatic detection of the most common incidents (vehicles with abnormal speed, pedestrians or objects falling on the road, vehicles stopped on the shoulder, and detection of kamikaze vehicles). To achieve these goals, different tasks have been addressed: lane segmentation, identification of traffic directions, and elimination of unnecessary objects in the foreground. The proposed system has been tested on a collection of videos recorded in real scenarios with real traffic, including areas with different lighting. Self-adaptability (plug and play) to different scenarios has been tested using videos with significant scene changes. The achieved system can process a minimum of 80 video frames within the camera’s field of view, covering a distance of 400 m, all within a span of 12 s. This capability ensures that vehicles travelling at speeds of 120 km/h are seamlessly detected with more than enough margin. Additionally, our analysis has revealed a substantial improvement in incident detection with respect to previous approaches. Specifically, an increase in accuracy of 2–5% in automatic mode and 2–7% in semi-automatic mode. The proposed classifier module only needs 2.3 MBytes of GPU to carry out the inference, thus allowing implementation in low-cost devices. application/pdf https://uvadoc.uva.es/handle/10324/68101 eng MDPI Security Systems and Data Security Artificial intelligence Traffic safety Seguridad en carretera Automobiles - Safety appliances Seguridad vial Tráfico, Ingeniería del - Informática Highway communications Machine learning Aprendizaje automático Self-adaptive software Video surveillance Video Artificial intelligence 1203.04 Inteligencia Artificial 1203.25 Diseño de Sistemas Sensores A self-adaptive automatic incident detection system for road surveillance based on deep learning info:eu-repo/semantics/article TEXT UVaDOC. Repositorio Documental de la Universidad de Valladolid Hispana