CASIA OpenIR  > 模式识别国家重点实验室  > 模式分析与学习
Traffic Sign Detection from Video: A Fast Approach with Tracking
Wang Dongdong; Hou Xinwen; Liu Cheng-Lin
2015-12
Conference Name3rd Asian Conference on Pattern Recognition
Source PublicationAsian Conference on Pattern Recognition
Conference Date2015-12-3-2015-12-6
Conference Place马来西亚吉隆坡
Abstract
This paper proposes a fast approach for traffic sign detection from video. First, we modify the image-based detector HHVCas to improve its accuracy and speed, then apply it to video-based detection with further acceleration by tracking. For the image-based detector, by optimizing the parameters in the cascade using an unsupervised approach, we achieve performance comparable to the state-of-the-art while keeping the speed advantage. Parallelizing some steps in the HHVCas detector leads to 1:5x speedup and 20fps detection. In video, the detector achieves 2.8x speedup and performs 35 fps by tracking every other frame. It also obtains significant precision increase by 5~8% at high recall when exploiting temporal coherence of results in multiple frames.
 
KeywordTraffic Sign Detection Tracking
Subject Area模式识别与智能系统
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11767
Collection模式识别国家重点实验室_模式分析与学习
Corresponding AuthorWang Dongdong
Affiliation中科院自动化研究所
Recommended Citation
GB/T 7714
Wang Dongdong,Hou Xinwen,Liu Cheng-Lin. Traffic Sign Detection from Video: A Fast Approach with Tracking[C],2015.
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