CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Image category learning and classification via optimal linear combination of multiple partially matching kernels
Fu, Si-Yao1; Yang, Guo-Sheng1; Hou, Zeng-Guang2
Source PublicationSOFT COMPUTING
2010
Volume14Issue:2Pages:181-192
SubtypeArticle
AbstractMultiple kernel learning (MKL) aims at simultaneously optimizing kernel weights while training the support vector machine (SVM) to get satisfactory classification or regression results. Recent publications and developments based on SVM have shown that by using MKL one can enhance interpretability of the decision function and improve classifier performance, which motivates researchers to explore the use of homogeneous model obtained as linear combination of various types of kernels. In this paper, we show that MKL problems can be solved efficiently by modified projection gradient method and applied for image categorization and object detection. The kernel is defined as a linear combination of feature histogram function that can measure the degree of similarity of partial correspondence between feature sets for discriminative classification, which allows recognition robust to within-class variation, pose changes, and articulation. We evaluate our proposed framework on the ETH-80 dataset for several multi-level image encodings for supervised and unsupervised object recognition and report competitive results.
KeywordMachine Learning Object Recognition Kernel Based Learning Pyramid Match Kernel
WOS HeadingsScience & Technology ; Technology
WOS KeywordRECOGNITION
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000269863700011
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/3445
Collection复杂系统管理与控制国家重点实验室_先进机器人
Affiliation1.Cent Univ Nationalities, Sch Informat & Engn, Beijing 100081, Peoples R China
2.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Fu, Si-Yao,Yang, Guo-Sheng,Hou, Zeng-Guang. Image category learning and classification via optimal linear combination of multiple partially matching kernels[J]. SOFT COMPUTING,2010,14(2):181-192.
APA Fu, Si-Yao,Yang, Guo-Sheng,&Hou, Zeng-Guang.(2010).Image category learning and classification via optimal linear combination of multiple partially matching kernels.SOFT COMPUTING,14(2),181-192.
MLA Fu, Si-Yao,et al."Image category learning and classification via optimal linear combination of multiple partially matching kernels".SOFT COMPUTING 14.2(2010):181-192.
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