LoRFT: Benchmarking Long-Range Vehicle Trajectory Reconstruction from Fixed Highway Cameras

• URL: http://arxiv.org/abs/2607.19911v1
• Date: Wed, 22 Jul 2026 08:42:58 GMT
• Title: LoRFT: Benchmarking Long-Range Vehicle Trajectory Reconstruction from Fixed Highway Cameras
• Abstract summary: We introduce LoRFT, to our knowledge the first open benchmark dedicated to long-range vehicle trajectory reconstruction from fixed highway cameras.<n>LoRFT comprises 22889 surveillance scenes, 366,109 video frames, 6,601 manually verified trajectories, 2,694 bounding boxes, road-geometry annotations, scene-level splits, and evaluation scripts.<n>We propose MapR-STNet, a map-aware residual sequence-to-sequence model that reconstructs distant trajectories in a road-geometry-aligned state space and dynamically refreshes local road geometry during decoding.
• Score: 6.806850352750748
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Long-range vehicle trajectories provide important spatio-temporal evidence for traffic safety analysis, autonomous driving evaluation, and data-driven traffic management, yet continuously recovering them from fixed highway cameras remains difficult. As vehicles recede into distant road regions, perspective compression and scale decay often fragment or prematurely terminate automatic tracklets, even when their continuation remains identifiable from motion consistency across neighboring frames. We formulate this problem as recovering the far-range continuation of a vehicle trajectory from a reliable near-field tracklet. We introduce LoRFT, to our knowledge the first open benchmark dedicated to long-range vehicle trajectory reconstruction from fixed highway cameras. LoRFT comprises 22 expressway surveillance scenes, 366,109 video frames, 6,601 manually verified trajectories, 2,694,889 bounding boxes, road-geometry annotations, scene-level splits, and evaluation scripts. We further propose Map-RSTNet, a map-aware residual sequence-to-sequence model that reconstructs distant trajectories in a road-geometry-aligned state space and dynamically refreshes local road geometry during decoding. On LoRFT, Map-RSTNet reduces ADE, FDE, and 5-second RMSE by 11.0%, 15.4%, and 10.5%, respectively, relative to the strongest baseline. These results demonstrate that road-geometry-aware reconstruction can extend usable trajectory records from existing fixed-camera infrastructure. LoRFT provides a reproducible testbed for long-range vehicle trajectory reconstruction.

Related papers

• A Geometry-Informed Computer Vision Method for Detecting and Examining Overtaking Vehicles From A Bicycle [0.0]
  We present a geometry-informed computer vision pipeline that automates overtaking event detection from a single bicycle-mounted camera.<n>The pipeline achieved 97.8% recall with zero false positives and identified overtaking intentions a mean of 2.44 seconds before vehicle passage.
  arXiv  Detail & Related papers  (2026-06-03T17:41:00Z)
• Mobile Traffic Camera Calibration from Road Geometry for UAV-Based Traffic Surveillance [0.1019561860229868]
  Raw UAV video is difficult to use for traffic analytics because vehicle motion is observed in perspective image coordinates.<n>This paper presents a lightweight pipeline for converting monocular UAV traffic video into a local metric bird's-eye-view representation.
  arXiv  Detail & Related papers  (2026-05-12T10:14:43Z)
• Robust Localization for Autonomous Vehicles in Highway Scenes [5.294056268363123]
  We propose a robust localization system to address highway challenges.<n>System uses a dual-likelihood LiDAR front end that decouples 3D geometric structures and 2D road-texture cues to handle environment changes.<n>An automated offline mapping and ground-truth pipeline keep maps fresh at high cadence for optimal localization performance.
  arXiv  Detail & Related papers  (2026-04-23T19:54:21Z)
• Measuring Braking Behavior Using Vehicle Tracking and Camera-to-Satellite Homography Rectification [4.61803711540329]
  This paper presents an open-source software application for analyzing traffic camera footage, focusing on vehicle behavior and braking events at signalized urban highways.<n>The core innovation is a robust ground-plane homography estimation that links fixed traffic camera views to satellite orthoimagery.<n>All detection and trajectory data are stored in a ClickHouse database for subsequent analysis.
  arXiv  Detail & Related papers  (2026-01-24T18:59:32Z)
• Road Obstacle Video Segmentation [71.92123495914892]
  We demonstrate that the road-obstacle segmentation task is inherently temporal, since the segmentation maps for consecutive frames are strongly correlated.<n>Our approach establishes a new state-of-the-art in road-obstacle video segmentation for long-range video sequences.
  arXiv  Detail & Related papers  (2025-09-16T15:34:43Z)
• Neural Semantic Map-Learning for Autonomous Vehicles [85.8425492858912]
  We present a mapping system that fuses local submaps gathered from a fleet of vehicles at a central instance to produce a coherent map of the road environment. Our method jointly aligns and merges the noisy and incomplete local submaps using a scene-specific Neural Signed Distance Field. We leverage memory-efficient sparse feature-grids to scale to large areas and introduce a confidence score to model uncertainty in scene reconstruction.
  arXiv  Detail & Related papers  (2024-10-10T10:10:03Z)
• Monocular BEV Perception of Road Scenes via Front-to-Top View Projection [57.19891435386843]
  We present a novel framework that reconstructs a local map formed by road layout and vehicle occupancy in the bird's-eye view. Our model runs at 25 FPS on a single GPU, which is efficient and applicable for real-time panorama HD map reconstruction.
  arXiv  Detail & Related papers  (2022-11-15T13:52:41Z)
• SRRT: Exploring Search Region Regulation for Visual Object Tracking [58.68120400180216]
  We propose a novel tracking paradigm, called Search Region Regulation Tracking (SRRT) SRRT applies a proposed search region regulator to estimate an optimal search region dynamically for each frame. On the large-scale LaSOT benchmark, SRRT improves SiamRPN++ and TransT with absolute gains of 4.6% and 3.1% in terms of AUC.
  arXiv  Detail & Related papers  (2022-07-10T11:18:26Z)
• Real Time Monocular Vehicle Velocity Estimation using Synthetic Data [78.85123603488664]
  We look at the problem of estimating the velocity of road vehicles from a camera mounted on a moving car. We propose a two-step approach where first an off-the-shelf tracker is used to extract vehicle bounding boxes and then a small neural network is used to regress the vehicle velocity.
  arXiv  Detail & Related papers  (2021-09-16T13:10:27Z)
• Phase Space Reconstruction Network for Lane Intrusion Action Recognition [9.351931162958465]
  In this paper, we propose a novel object-level phase space reconstruction network (PSRNet) for motion time series classification. Our PSRNet could reach the best accuracy of 98.0%, which remarkably exceeds existing action recognition approaches by more than 30%.
  arXiv  Detail & Related papers  (2021-02-22T16:18:35Z)
• Road Curb Detection and Localization with Monocular Forward-view Vehicle Camera [74.45649274085447]
  We propose a robust method for estimating road curb 3D parameters using a calibrated monocular camera equipped with a fisheye lens. Our approach is able to estimate the vehicle to curb distance in real time with mean accuracy of more than 90%.
  arXiv  Detail & Related papers  (2020-02-28T00:24:18Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.