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BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation
Han, Zhizhong1; Liu, Zhenbao2; Vong, Chi-Man3; Liu, Yu-Shen1; Bu, Shuhui2; Han, Junwei2; Chen, C. L. Philip4
2017-08
Source PublicationIEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN1057-7149
Volume26Issue:8Pages:3707-3720
Abstract

Highly discriminative 3D shape representations can be formed by encoding the spatial relationship among virtual words into the Bag of Words (BoW) method. To achieve this challenging task, several unresolved issues in the encoding procedure must be overcome for 3D shapes, including: 1) arbitrary mesh resolution; 2) irregular vertex topology; 3) orientation ambiguity on the 3D surface; and 4) invariance to rigid and non-rigid shape transformations. In this paper, a novel spatially enhanced 3D shape representation called bag of spatial context correlations (BoSCCs) is proposed to address all these issues. Adopting a novel local perspective, BoSCC is able to describe a 3D shape by an occurrence frequency histogram of spatial context correlation patterns, which makes BoSCC become more compact and discriminative than previous global perspective-based methods. Specifically, the spatial context correlation is proposed to simultaneously encode the geometric and spatial information of a 3D local region by the correlation among spatial contexts of vertices in that region, which effectively resolves the aforementioned issues. The spatial context of each vertex is modeled by Markov chains in a multi-scale manner, which thoroughly captures the spatial relationship by the transition probabilities of intra-virtual words and the ones of inter-virtual words. The high discriminability and compactness of BoSCC are effective for classification and retrieval, especially in the scenarios of limited samples and partial shape retrieval. Experimental results show that BoSCC outperforms the state-of-the-art spatially enhanced BoW methods in three common applications: global shape retrieval, shape classification, and partial shape retrieval.

KeywordBag Of Spatial Context Correlations Spatial Context Correlation Spatial Context 3d Shape Representations
DOI10.1109/TIP.2017.2704426
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000403819200005
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
The Source to ArticleWOS
Fulltext Access
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Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Tsinghua University, Beijing, China
2.Northwestern Polytechnical University, Xi’an, China
3.Department of Computer and Information Science, University of Macau, Macau, China
4.Faculty of Science and Technology, University of Macau, Macau, China
Recommended Citation
GB/T 7714
Han, Zhizhong,Liu, Zhenbao,Vong, Chi-Man,et al. BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2017,26(8):3707-3720.
APA Han, Zhizhong.,Liu, Zhenbao.,Vong, Chi-Man.,Liu, Yu-Shen.,Bu, Shuhui.,...&Chen, C. L. Philip.(2017).BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation.IEEE TRANSACTIONS ON IMAGE PROCESSING,26(8),3707-3720.
MLA Han, Zhizhong,et al."BoSCC: Bag of Spatial Context Correlations for Spatially Enhanced 3D Shape Representation".IEEE TRANSACTIONS ON IMAGE PROCESSING 26.8(2017):3707-3720.
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