NDLI: Image retrieval using object template

Content Provider	IEEE Xplore Digital Library
Author	Li-Qun Zhang Zreng-Xing Sun Bin-Bin Peng Hui-Feng Wang
Copyright Year	2002
Description	Author affiliation: State Key Lab for Novel Software Technol., Nanjing Univ., China (Li-Qun Zhang; Zreng-Xing Sun; Bin-Bin Peng; Hui-Feng Wang)
Abstract	How to mine, organize and use the information of the objects in an image, which can just reflect the user's intension precisely, is overlooked for a long time. From the point of view of mining, training and utilizing such information efficiently, this paper focuses on a particular group of features for every class of object. With this group of features, the class of object can be separated with others most distinctly. Based on this idea, using SVM (Support Vector Machine), HGM (Hybrid Gauss Model), PCA (principle component analysis) and FFC (Forward Feature Combination), we design and implement an Object Template that can represent a kind of object (such as tiger) perfectly and then present its two applications. With our Object Template, the Recall Precision (P100) for image retrieval can be increased to 46.175%; the precision of Object Detection also reaches 82.832%. (On 3400 real-world image collections).
Sponsorship	Hebei Univ. IEEE Syst., Man & Cybernetics Tech. Committe on Cybernetics
Starting Page	2090
Ending Page	2096
File Size	432606
Page Count	7
File Format	PDF
ISBN	0780375084
DOI	10.1109/ICMLC.2002.1175407
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image retrieval Image segmentation Image databases Machine learning Gaussian distribution Histograms Prototypes Robustness Information retrieval Bridges
Content Type	Text
Resource Type	Article

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