NDLI: Image collection summarization via dictionary learning for sparse representation

Content Provider	IEEE Xplore Digital Library
Author	Chunlei Yang Jinye Peng Jianping Fan
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, University of North Carolina, Charlotte, NC 28223, USA (Chunlei Yang) \|\| School of Information Science and Technology, Northwest University, Xi'an 710069, China (Jinye Peng; Jianping Fan)
Abstract	In this paper, a novel framework is developed to achieve effective summarization of large-scale image collection by treating the problem of automatic image summarization as the problem of dictionary learning for sparse representation, e.g., the summarization task can be treated as a dictionary learning task (i.e., the given image set can be reconstructed sparsely with this dictionary). For image set of a specific category or a mixture of multiple categories, we have built a sparsity model to reconstruct all its images by using a subset of most representative images (i.e., image summary); and we adopted the simulated annealing algorithm to learn such sparse dictionary by minimizing an explicit optimization function. By investigating their reconstruction ability under sparsity constrain and diversity constrain, we have quantitatively measure the performance of various summarization algorithms. Our experimental results have shown that our dictionary learning for sparse representation algorithm can obtain more accurate summary as compared with other baseline algorithms.
Starting Page	1122
Ending Page	1129
File Size	250869
Page Count	8
File Format	PDF
ISBN	9781467312264
ISSN	10636919
e-ISBN	9781467312288
e-ISBN	9781467312271
DOI	10.1109/CVPR.2012.6247792
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Image reconstruction Visualization Clustering algorithms Encoding Simulated annealing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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