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Indexed by:会议论文

Date of Publication:2018-01-01

Included Journals:CPCI-S

Volume:2

Key Words:ancient architecture feature; smartphone; realtime object detection; deep learning; convolution neural network; SSD-Mobilenet

Abstract:Due to the particularity of texture features in ancient buildings, which refers to the fact that these features have a high historical and artistic value, it is of great significance to identify and count them. However, the complexity and large number of textures are a big challenge for the artificial identification statistics. In order to overcome these challenges, this paper proposes an approach that uses smartphones to achieve a realtime detection of ancient buildings' features. The training process is based on SSD-Mobilenet, which is a kind of Convolutional Neural Network (CNN). The results show that this method shows well performance in reality and can indeed detect different ancient building features in real time.