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arXiv:2604. 23814v2 Announce Type: replace-cross Abstract: Urban environments contain many imaging sensors built for specific purposes, including ATM, body-worn, CCTV, and dashboard cameras.
arXiv:2609.34302v2 Announce Type: replace Abstract: Multi-camera pedestrian localization is useful for wide-area monitoring in public and commercial spaces. However, deploying these systems often req...
The paper introduces a multi-vehicle dataset that includes camera, LiDAR, and radar sensor data along with scanned 3D models of all vehicles. Each vehicle’s pose and continuous kinematics are provided via RTK‑GNSS, enabling precise knowledge of the dynamic surroundings at any time. The dataset supports single‑ and multi‑object recordings with seven target vehicles, allowing evaluation of measurement effects such as occlusion and reflections thanks to known vehicle surface normals.
arXiv:2609.01584v1 Announce Type: new Abstract: Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traf...
arXiv:2606. 00119v1 Announce Type: cross Abstract: Reliable work zone mapping is important for connected and autonomous vehicles (CAVs) to navigate safely and smoothly through work zone areas.
The paper presents a smartphone-based system that uses computer vision to automatically estimate vehicle speed and identify vehicles by license plate, make/model, and color. Experiments on a Brazilian dataset and real-world recordings in Austin, Texas show moderate recognition rates: 46% for license plates, 60.8% for color, 48.6% for make, and 16.89% for make/model. The study also discusses legal, technological, and practical considerations for deploying such smartphone recordings in traffic enforcement.