@article{ref1,
title="Vision-based bicycle detection using multiscale block local binary pattern",
journal="Mathematical problems in engineering",
year="2014",
author="Hu, Hongyu and Tao, Pengfei and Gao, Zhenhai and Wang, Qingnian and Li, Zhihui and Qu, Zhaowei",
volume="",
number="",
pages="370685-370685",
abstract="Bicycle traffic has heavy proportion among all travel modes in some developing countries, which is crucial for urban traffic control and management as well as facility design. This paper proposes a real-time multiple bicycle detection algorithm based on video. At first, an effective feature called multiscale block local binary pattern (MBLBP) is extracted for representing the moving object, which is a well-classified feature to distinguish between bicycles and nonbicycles; then, a cascaded bicycle classifier trained by AdaBoost algorithm is proposed, which has a good computation efficiency. Finally, the method is tested with video sequence captured from the real-world traffic scenario. The bicycles in the test scenario are successfully detected.<p /><p>Language: en</p>",
language="en",
issn="1024-123X",
doi="10.1155/2014/370685",
url="http://dx.doi.org/10.1155/2014/370685"
}