Pedestrian Detection Algorithm Based on the Improved SSD

In recent years, pedestrian detection is a hot research topic in the field of computer vision and artificial intelligence, It is widely used in the fields of automatic driving safety and security and pedestrian analysis. But pedestrians as transfigure change target, and because the pedestrian dress differ in thousands ways, lead to the traditional pedestrian detection technology detection accuracy is not high, it restricts the development of pedestrian detection technology. With the development of deep learning, the pedestrian detection method based on deep learning greatly improves the accuracy of pedestrian detection. For the problem of low detection accuracy of small targets in SSD, this paper proposes an improved SSD pedestrian detection method based on the context information, by extracting the shallow features in the SSD convolutional neural network, fuses the shallow semantic information in the convolutional layer with the deep semantic information, and then detects the size of the pedestrian in the image. Features Redesigned pre-selection boxes with different aspect ratios, improve the SSD model test result is superior to the standard model of the SSD.