English

Obstacle Detection Quality as a Problem-Oriented Approach to Stereo Vision Algorithms Estimation in Road Situation Analysis

Computer Vision and Pattern Recognition 2019-01-04 v1

Abstract

In this work we present a method for performance evaluation of stereo vision based obstacle detection techniques that takes into account the specifics of road situation analysis to minimize the effort required to prepare a test dataset. This approach has been designed to be implemented in systems such as self-driving cars or driver assistance and can also be used as problem-oriented quality criterion for evaluation of stereo vision algorithms.

Keywords

Cite

@article{arxiv.1809.02228,
  title  = {Obstacle Detection Quality as a Problem-Oriented Approach to Stereo Vision Algorithms Estimation in Road Situation Analysis},
  author = {A. A. Smagina and D. A. Shepelev and E. I. Ershov and A. S. Grigoryev},
  journal= {arXiv preprint arXiv:1809.02228},
  year   = {2019}
}
R2 v1 2026-06-23T03:57:22.038Z