Spatial Scene Matching Based on Multilevel Relevance Feedback

CHEN Zhanlong; ZHANG Dingwen; XIE Zhong; WU Liang

doi:10.13203/j.whugis20160360

Volume 43 Issue 9

Sep. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(9): 1422-1428. > DOI: 10.13203/j.whugis20160360

CHEN Zhanlong, ZHANG Dingwen, XIE Zhong, WU Liang. Spatial Scene Matching Based on Multilevel Relevance Feedback[J]. Geomatics and Information Science of Wuhan University, 2018, 43(9): 1422-1428. DOI: 10.13203/j.whugis20160360

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Spatial Scene Matching Based on Multilevel Relevance Feedback

1.
Department of Information Engineering, China University of Geosciences(Wuhan), Wuhan 430074, China

Funds:

The National Key R & D Program of China 2017YFC0602204

the National Natural Science Foundation of China 41401443

the National Natural Science Foundation of China 41671400

the Natural Science Foundation of Hubei Province 2015CFA012

the Fundamental Research Funds for the Central Universities CUG160226

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Author Bio:
CHEN Zhanlong, PhD, associate professor, specializes in GIS theory research, geo-computation and spatial analysis, high performance computation. E-mail:Chenzhanlong2005@126.com
Corresponding author:
ZHANG Dingwen, PhD. E-mail:dingwenzhang@yahoo.com
Received Date: September 12, 2017
Published Date: September 04, 2018

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Abstract

Abstract

Existing spatial scene matching methods try to use low level features such as local geome-trical shape descriptors, binary spatial relations of cardinal directions or topology and so on to meet with the high level description demands from users, and lack the feedback mechanism of user subjective concepts. This paper applies the feedback relevance mechanism to spatial scene matching, analyzes the effects after studying users' needs, and then evaluates the relevance of matching results to the desired spatial scene. According to the feedback, the retrieval model updates the weights of descriptors to simulate user's perception, as a result, the retrieval fits the users' requirements much better. The experiment verifies the efficiency and feasibility by users survey and weights convergence. Experimental result shows that spatial scene matching based on multilevel relevance feedback has a high user subjectivity and accords with human's cognizance. In addition, users could obtain satisfactory result by two or three iterations.
- spatial scene,
- spatial matching,
- multilevel relevance feedback,
- weight updating

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