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Dual-Layer Density Estimation for Multiple Object Instance Detection
Zhang Q(张强); Qu DK(曲道奎); Xu F(徐方); Jia K(贾凯); Sun, Xueying
Department其他
Source PublicationJOURNAL OF SENSORS
ISSN1687-725X
2016
Pages1-12
Indexed BySCI ; EI
EI Accession number20164002871739
WOS IDWOS:000383462600001
Contribution Rank1
Funding OrganizationShenyang SIASUN Robot Automation Co., Ltd. ; National Key Technology R&D Program, China [2015BAF13B00]
AbstractThis paper introduces a dual-layer density estimation-based architecture for multiple object instance detection in robot inventory management applications. The approach consists of raw scale-invariant feature transform (SIFT) feature matching and key point projection. The dominant scale ratio and a reference clustering threshold are estimated using the first layer of the density estimation. A cascade of filters is applied after feature template reconstruction and refined feature matching to eliminate false matches. Before the second layer of density estimation, the adaptive threshold is finalized by multiplying an empirical coefficient for the reference value. The coefficient is identified experimentally. Adaptive threshold-based grid voting is applied to find all candidate object instances. Error detection is eliminated using final geometric verification in accordance with Random Sample Consensus (RANSAC). The detection results of the proposed approach are evaluated on a self-built dataset collected in a supermarket. The results demonstrate that the approach provides high robustness and low latency for inventory management application.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectEngineering, Electrical & Electronic ; Instruments & Instrumentation
WOS KeywordRECOGNITION ; FEATURES ; SPACE
WOS Research AreaEngineering ; Instruments & Instrumentation
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/19239
Collection其他
Corresponding AuthorZhang Q(张强)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China
2.University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China
3.SIASUN Robot and Automation Co., Ltd., No. 16 Jinhui Street, Hunnan New District, Shenyang, 110168, China
4.Department of Information Service and Intelligent Control, Chinese Academy of Sciences, No. 114 Nanta Street, Shenhe District, Shenyang 110016, China
Recommended Citation
GB/T 7714
Zhang Q,Qu DK,Xu F,et al. Dual-Layer Density Estimation for Multiple Object Instance Detection[J]. JOURNAL OF SENSORS,2016:1-12.
APA Zhang Q,Qu DK,Xu F,Jia K,&Sun, Xueying.(2016).Dual-Layer Density Estimation for Multiple Object Instance Detection.JOURNAL OF SENSORS,1-12.
MLA Zhang Q,et al."Dual-Layer Density Estimation for Multiple Object Instance Detection".JOURNAL OF SENSORS (2016):1-12.
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