Vehicle Detection Method Based on SSD

doi:10.3969/j.issn.1006-2475.2019.05.007

Abstract

Abstract: The traditional vehicle target detection algorithm needs to select appropriate features for different image scenes, resulting in poor generalization ability. Therefore, an image detection method based on SSD (Single Shot MultiBox Detector) for vehicle is proposed. The method detects the vehicle by predicting the convolutional feature maps of multiple scales, and improves the detection accuracy of the vehicle to a certain extent. The small defects of the original SSD method in the training process are found, and the loss function is improved to optimize the training speed. Finally, the KITTI data set is used for training. The experimental results show that the method has a higher recognition rate for vehicles and the effect is better than traditional algorithms.

Key words: vehicle, target detection, SSD, convolutional neural network

CLC Number:

TP391.4

WU Shui-qing, WANG Yu, SHI Yan. Vehicle Detection Method Based on SSD[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.05.007.

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