Fast Car Detection Using Image Strip Features
Abstract
This paper presents a fast method for detecting multi-view cars in real-world scenes. Cars are artificial objects with various appearance changes, but they have relatively consistent characteristics in structure that consist of some basic local elements. Inspired by this, we propose a novel set of image strip features to describe the appearances of those elements. The new features represent various types of lines and arcs with edge-like and ridge-like strip patterns, which significantly enrich the simple features such as haar-like features and edgelet features. They can also be calculated efficiently using the integral image. Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features. The experimental results on widely used single view and multi-view car datasets show that our approach is fast and has good performance.
Cite
Text
Zheng and Liang. "Fast Car Detection Using Image Strip Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206642Markdown
[Zheng and Liang. "Fast Car Detection Using Image Strip Features." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/zheng2009cvpr-fast/) doi:10.1109/CVPR.2009.5206642BibTeX
@inproceedings{zheng2009cvpr-fast,
title = {{Fast Car Detection Using Image Strip Features}},
author = {Zheng, Wei and Liang, Luhong},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2009},
pages = {2703-2710},
doi = {10.1109/CVPR.2009.5206642},
url = {https://mlanthology.org/cvpr/2009/zheng2009cvpr-fast/}
}