CASIA OpenIR  > 类脑智能研究中心
Incremental Codebook Adaptation for Visual Representation and Categorization
Zhang CJ(张淳杰); Cheng J(程健); Tian Q(田奇)
Source PublicationIEEE Transactions on Cybernetics
2017
Issue0Pages:0
AbstractThe bag-of-visual-words model is widely used for visual content analysis. For visual data, the codebook plays an important role for efficient representation. However, the codebook has to be re-learned with the changes of training images. Once the codebook is changed, the encoding parameters of local features have to be re-computed. To alleviate this problem, in this paper, we propose an incremental codebook adaptation method for efficient visual representation. Instead of learning a new codebook, we gradually adapt a pre-learned codebook using new images in an incremental way. To make use of the pre-learned codebook, we try to make changes to the pre-learned codebook with sparsity constraint and low-rank correlation. Besides, we also encode visually similar local features within a neighborhood to take advantage of locality information and ensure the encoded parameters are consistent. To evaluate the effectiveness of the proposed method, we apply the proposed method for categorization tasks on several public image datasets. Experimental results prove the effectiveness and usefulness of the proposed method over other codebook based methods.
KeywordCodebook Learning Visual Representation Low-rank Sparse Coding
DOI10.1109/TCYB.2017.2726079
WOS IDWOS:000435342100006
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15319
Collection类脑智能研究中心
Affiliation1.Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
3.Department of Computer Sciences, University of Texas at San Antonio. TX, 78249-1604, U.S.A.
Recommended Citation
GB/T 7714
Zhang CJ,Cheng J,Tian Q. Incremental Codebook Adaptation for Visual Representation and Categorization[J]. IEEE Transactions on Cybernetics,2017(0):0.
APA Zhang CJ,Cheng J,&Tian Q.(2017).Incremental Codebook Adaptation for Visual Representation and Categorization.IEEE Transactions on Cybernetics(0),0.
MLA Zhang CJ,et al."Incremental Codebook Adaptation for Visual Representation and Categorization".IEEE Transactions on Cybernetics .0(2017):0.
Files in This Item: Download All
File Name/Size DocType Version Access License
07990530.pdf(2354KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
t-cyber 录用邮件.pdf(130KB) 开放获取--View Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang CJ(张淳杰)]'s Articles
[Cheng J(程健)]'s Articles
[Tian Q(田奇)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang CJ(张淳杰)]'s Articles
[Cheng J(程健)]'s Articles
[Tian Q(田奇)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang CJ(张淳杰)]'s Articles
[Cheng J(程健)]'s Articles
[Tian Q(田奇)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 07990530.pdf
Format: Adobe PDF
File name: t-cyber 录用邮件.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.