Research of road scene object detection algorithm based on mobile platform

Yujia Chen; Xiaoning Liu; Chongwen Wang

doi:10.1117/12.2574416

24 June 2020 Research of road scene object detection algorithm based on mobile platform

Yujia Chen, Xiaoning Liu, Chongwen Wang

Proceedings Volume 11526, Fifth International Workshop on Pattern Recognition; 1152606 (2020) https://doi.org/10.1117/12.2574416
Event: Fifth International Workshop on Pattern Recognition, 2020, Chengdu, China

Abstract

There are many object detection methods in terms of object recognition based on traditional methods, but they are not sufficient to meet the demand for accuracy and speed in real-life scenarios. And compared with mobile platform, cloud service is also not conducive to the use in practical scenarios. Therefor we optimize the YOLO (You Only Look Once, a method for real-time detection of objects) algorithm through renormalization processing, build the Chinese road sign dataset and perform random affine transformation, random blur, and brightness transformation processing on the dataset to enhance the generalization ability of the final model. The parameters of the model are fine-tuned to reduce the period required to train the model and improve the performance of deep learning. Finally, the deep learning model of object detection will be transplanted to iOS mobile terminal to meet the requirements of real-time and accuracy in automatic driving scenarios. We identifie three types of road objects. The detection accuracy of pedestrians on road scenes reaches 75.9%, and the average detection accuracy of buses, cars, bicycles, and motorcycles is 72%. The detection accuracy of road signs is 69%. Total accuracy is 74.31%. The average detection rate of running tests on mobile phones is 12.5 frames per second.

Citation Download Citation

Yujia Chen, Xiaoning Liu, and Chongwen Wang "Research of road scene object detection algorithm based on mobile platform", Proc. SPIE 11526, Fifth International Workshop on Pattern Recognition, 1152606 (24 June 2020); https://doi.org/10.1117/12.2574416

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KEYWORDS

Roads

Detection and tracking algorithms

Data modeling

Target detection

Image processing

Information operations

Data conversion

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