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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 18: AAAI-21 Student Papers and Demonstrations

Information Block Detection in Infographic Based on Spatial Proximity and Structural Similarity (Student Abstract)

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Abstract:

The infographic is a type of visualization chart used to display information. Existing infographic understanding works utilize spatial proximity to group elements into information blocks. However, these works ignore structural features such as background color and boundary, which results in poor performance towards complex infographic. We propose Spatial and Structural Feature Extraction model to group elements based on spatial proximity and structural similarity. We introduce a new dataset towards information block detection. Experiments show that our model can effectively identify the information blocks in the infographic.

Authors

Jie Lin

School of Software Engineering, South China University of Technology, Guangzhou, China Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education


Xin Wu

School of Software Engineering, South China University of Technology, Guangzhou, China Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education


Jianwei Lu

School of Software Engineering, South China University of Technology, Guangzhou, China Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education


Yi Cai

School of Software Engineering, South China University of Technology, Guangzhou, China Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education


DOI:

10.1609/aaai.v35i18.17911