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AssigneeBeijing University of Civil Engineering and Architecture
InventorsYuefang Rong, Yue Hu, Haoxi Lin, Mengyuan Jia, Xin Yan, Jian Song, Siwei Guo, Haoran Zhang, Yunqian Chen, Jijia Jiang, Zheng Ma, Xinxin Liu, Zilin Wang, Xiaohang Liang, Shuhan Guo
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A quantitative analysis method for spatial elements in high-intensity urban areas based on image data includes: obtaining a panoramic street view image from observation points in a selected high-intensity urban area; extracting, based on vision inspection technology, shallow features from the panoramic street view image; obtaining deep features in the panoramic street view image through a deep learning model; constructing, based on topological analysis, a topological graph of the spatial elements by registering each shallow and deep feature with predefined logical rules; and inputting the topological graph to a classification model which is pre-trained, and outputting, by the classification model, classification results and a spatial distribution image of the spatial elements in the panoramic street view image. The method achieves multi-dimensional feature fusion by simultaneously utilizing the shallow and deep features, which improves the accuracy of classification and enhances the adaptability to multi category elements in complex scenes.
A quantitative analysis method for spatial elements in urban areas based on image data, comprising:
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