mlsanityData to 14 Oct 2026

Estimation of Vehicular Velocity based on Non-Intrusive stereo camera

arXiv 2304.05298 ↗First posted 11 Apr 2023cs.CV cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

The paper presents a modular approach for the estimation of a leading vehicle's velocity based on a non-intrusive stereo camera where SiamMask is used for leading vehicle tracking, Kernel Density estimate (KDE) is used to smooth the distance prediction from a disparity map, and LightGBM is used for leading vehicle velocity estimation. Our approach yields an RMSE of 0.416 which outperforms the baseline RMSE of 0.582 for the SUBARU Image Recognition Challenge

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 15 references that are in the map. First posted on arXiv 11 Apr 2023.

Builds on

4 of 15 references.

References · 4

  1. 2016Fully-Convolutional Siamese Networks for Object Trackingcited by 568
  2. 2018Fast Online Object Tracking and Segmentation: A Unifying Approachcited by 272
  3. 2015Learning Multi-Domain Convolutional Neural Networks for Visual Trackingcited by 209
  4. 2017Probabilistic Vehicle Trajectory Prediction over Occupancy Grid Map via Recurrent Neural Networkcited by 56

Built on by

Not cited yet.