DocumentCode :
146975
Title :
Plane Geometry Figure Retrieval with Bag of Shapes
Author :
Lu Liu ; Xiaoqing Lu ; Keqiang Li ; Jingwei Qu ; Liangcai Gao ; Zhi Tang
Author_Institution :
Inst. of Comput. Sci. & Technol., Peking Univ., Beijing, China
fYear :
2014
fDate :
7-10 April 2014
Firstpage :
1
Lastpage :
5
Abstract :
Digital education is serving an increasingly important function in most educational institutions, thus resulting in the production of a large number of digital documents online for education purposes. However, convenient ways to retrieve mathematic geometry questions are lacking because current retrieval systems largely rely on keywords instead of geometry figure images. This study focuses on plane geometry figure (PGF) image retrieval with the aim of retrieving relevant geometry images that contain more structural information than a question text stem. To fully use geometrical properties, a Bag-of-shapes (BoS) method is proposed to build the feature descriptor of an image. The BoS method contains either basic geometric primitives or dual-primitive structures along with several specific geometrical features for shape description. Based on the BoS feature descriptor, we apply cosine similarity with group feature weight as vector similarity measure for ranking to achieve high efficiency. For a PGF image query, the retrieval results are provided in an appropriate ranking order, which has high visual similarity with respect to human perception. Retrieval experiments and evaluation results show the effectiveness and efficiency of the proposed BoS shape descriptor.
Keywords :
computational geometry; image retrieval; BoS feature descriptor; BoS method; BoS shape descriptor; PGF image query; PGF image retrieval; appropriate ranking order; bag-of-shapes method; cosine similarity; digital documents; digital education; dual-primitive structures; educational institutions; geometry figure images; geometry image retrieval; human perception; mathematic geometry questions; plane geometry figure retrieval; question text stem; retrieval systems; shape description; vector similarity measure; visual similarity; Conferences; Feature extraction; Geometry; Image retrieval; Shape; Text analysis; bag-of-shapes; geometric structure; image retrieval; plane geometry figure; shape feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis Systems (DAS), 2014 11th IAPR International Workshop on
Conference_Location :
Tours
Print_ISBN :
978-1-4799-3243-6
Type :
conf
DOI :
10.1109/DAS.2014.53
Filename :
6824397
Link To Document :
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