A vehicle detection algorithm in complex traffic scenes

Tianyu Jin; Dengyin Zhang; Fei Ding; Zhen Zhang; Min Zhang

doi:10.1117/12.2573189

12 June 2020 A vehicle detection algorithm in complex traffic scenes

Tianyu Jin, Dengyin Zhang, Fei Ding, Zhen Zhang, Min Zhang

Proceedings Volume 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020); 115190C (2020) https://doi.org/10.1117/12.2573189
Event: Twelfth International Conference on Digital Image Processing, 2020, Osaka, Japan

Abstract

In complex traffic scenarios, there are many problems such as inaccurate vehicle positioning, low recognition rate, and missed detection of vehicles for instability of the traffic environment. This paper proposes an improved Faster R-CNN algorithm for accurate vehicle detection. We use feature maps of depth images to supplement vehicle details by adding a depth channel into the detection model. When training the model, we add a hard sample mining strategy. We evaluate our newly proposed approach using KITTI dataset. The experimental results show that our proposed approach has a significant improvement in recognition accuracy by 5%.

Citation Download Citation

Tianyu Jin, Dengyin Zhang, Fei Ding, Zhen Zhang, and Min Zhang "A vehicle detection algorithm in complex traffic scenes", Proc. SPIE 11519, Twelfth International Conference on Digital Image Processing (ICDIP 2020), 115190C (12 June 2020); https://doi.org/10.1117/12.2573189

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KEYWORDS

Detection and tracking algorithms

RGB color model

Convolution

Image fusion

Statistical modeling

Mining

Target detection

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