ML Anthology

Fast Vehicle Detection with Probabilistic Feature Grouping and Its Application to Vehicle Tracking

Zu Whan Kim, Jitendra Malik
ICCV 2003 pp. 524-531
doi:10.1109/ICCV.2003.1238392 /iccv/2003/kim2003iccv-fast/

Abstract

Generating vehicle trajectories from video data is an important application of ITS (intelligent transportation systems). We introduce a new tracking approach which uses model-based 3-D vehicle detection and description algorithm. Our vehicle detection and description algorithm is based on a probabilistic line feature grouping, and it is faster (by up to an order of magnitude) and more flexible than previous image-based algorithms. We present the system implementation and the vehicle detection and tracking results.

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Cite

Text

Kim and Malik. "Fast Vehicle Detection with Probabilistic Feature Grouping and Its Application to Vehicle Tracking." IEEE/CVF International Conference on Computer Vision, 2003. doi:10.1109/ICCV.2003.1238392

Markdown

[Kim and Malik. "Fast Vehicle Detection with Probabilistic Feature Grouping and Its Application to Vehicle Tracking." IEEE/CVF International Conference on Computer Vision, 2003.](https://mlanthology.org/iccv/2003/kim2003iccv-fast/) doi:10.1109/ICCV.2003.1238392

BibTeX

@inproceedings{kim2003iccv-fast,
  title     = {{Fast Vehicle Detection with Probabilistic Feature Grouping and Its Application to Vehicle Tracking}},
  author    = {Kim, Zu Whan and Malik, Jitendra},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2003},
  pages     = {524-531},
  doi       = {10.1109/ICCV.2003.1238392},
  url       = {https://mlanthology.org/iccv/2003/kim2003iccv-fast/}
}