An image collection abstract generation method in social media
An image collection and media technology, applied in still image data retrieval, still image data browsing/visualization, special data processing applications, etc., can solve the problems of non-existence of clustering algorithms, unstable results, redundant abstract images, etc. Achieve accurate feature matching, improve matching accuracy, and solve costly problems
Active Publication Date: 2018-08-10
HEFEI UNIV OF TECH
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The smaller the number of clusters, the simpler the calculation but the lower the accuracy of the data set division. The higher the number of clusters, the higher the accuracy of the data set division but the redundancy of the summary image.
[0006] Second, traditional clustering algorithms rely on initial cluster centers, so the results are often unstable
[0007] Third, an optimal clustering algorithm does not exist, and no clustering method is suitable for all data sets
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[0149] In order to verify the effect of the method in this patent, 100 queries were initiated on social media sites, and 100 data sets were established, each data set contains thousands or even tens of thousands of image samples. Use local SURF features, global color features and texture features to represent image information, use spatial constraint matrix and simplified random sampling consistency to perform geometric verification on matching pairs, and use validity indicators to judge the clustering effect of neighbor propagation, automatic cluster selection A set of optimally representative images serves as an image set summary.
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The invention discloses a method for generating abstracts of image collections under social media. Firstly, visual features of images in image collections under social media are extracted; then the extracted local features and global features are fused and matched; The spatial constraint relationship forms a spatial location map and a simplified geometric constraint representative data set to further filter out noise points; secondly, an automatic clustering model based on neighbor propagation is established; finally, a group of optimal clustering centers is found by using the clustering validity index. The present invention can make full use of the multi-modal features of images, and summarize a large number of related images in image collections under social media, so as to accurately generate a group of optimal representative images.
Description
technical field [0001] The invention relates to the field of analysis and retrieval of social media image collections, in particular to a method for generating abstracts of image collections under social media. Background technique [0002] With the rapid development of Internet technology and the wide application of multimedia technology, the status of the Internet has been continuously improved, and it has become the main platform for people to communicate and share information. Network users spontaneously contribute multimedia materials such as pictures and videos, and disseminate them through sharing, evaluation, discussion, etc., so that a large number of pictures flood into the network. In such a vast ocean of pictures, it is not easy to find the one we want. When we initiate a query, what is returned to us is a huge queue of multimedia picture sets, and there is a large amount of data with repeated or partially repeated content, as well as a considerable amount of da...
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IPC IPC(8): G06F17/30
CPCG06F16/54G06F18/21
Inventor 赵烨洪日昌汪萌刘学亮郝世杰
Owner HEFEI UNIV OF TECH
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