Feng Zhao
ABSTRACT
In view of the difficulty in crowd counting due to occlusion and unequal distribution in crowded scenes, this paper presents a people counting method based on scale adaptive network. In this method, the first ten sixteen-vgg layers are used to initially obtain the population characteristics; then the scale adaptive module designed by us is regarded as the main branch, which can extract the multi-scale population characteristics, and at this stage, the expansion convolution is introduced to further optimize the feature map; in order to effectively solve the occlusion problem between crowds, this paper designs a shallow convolution module as another branch, and fuses its output feature map with that of scale adaptive module. Finally, this paper selects representative datasets to test the method. The results show that in terms of mean absolute error (MAE) and mean square error (MSE), the proposed method is significantly lower than the comparison method.
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Index Terms
- Crowd Counting Method Based on Scale Adaptive Network
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