Cross-media sparse Hash indexing method

A hash index and cross-media technology, applied in the field of cross-media retrieval, can solve the problem that the time complexity cannot meet the online search needs of users

Inactive Publication Date: 2013-12-25
ZHEJIANG UNIV
View PDF3 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The time complexity of the traditional violent linear comparison strategy in the face of

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Cross-media sparse Hash indexing method
  • Cross-media sparse Hash indexing method
  • Cross-media sparse Hash indexing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0079] In order to verify the effect of the present invention, about 2,900 webpages are grabbed from the webpage of "Wikipedia-Daily Image", each webpage contains an image and several relevant description texts. Use this as a data set to experiment with cross-media sparse hash indexing. Experiments on cross-media retrieval on two types of media (image and text media) are given. For image modality data, the present invention extracts SIFT local features, and then uses K-means clustering method to cluster SIFT features to form 1000 center points. Finally, each image is quantified into a 1000-dimensional "Bag of visual words" (Bag of visual words); for text modal data, the most representative 5000 words are selected according to the word TF value to form a 5000-dimensional "word Bag" (Bag of words).

[0080] In order to objectively evaluate the performance of the algorithm of the present invention, the inventor uses the average accuracy rate (Mean Average Precision, MAP) and wh...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a cross-media sparse Hash indexing method. The method comprises the steps of (1) performing unified modeling on incidence relations among data of a plurality of modes through hyper-graphs; (2) learning dictionaries of the plurality of modes simultaneously through a dictionary learning frame, applying regular constraint to sparse and hyper-graph incidence relations and learning data of each mode to obtain corresponding dictionaries; (3) using the learned dictionaries as Hash functions, and performing Hash encoding on new data through corresponding mode dictionaries; (4) converting the Hash codes into sparse code sets through corresponding Hash strategies to change sparse code similarity calculation problems into the set similarity calculation problems, and performing similarity calculation through a similar jaccard distance measurement mode.

Description

technical field [0001] The invention relates to cross-media retrieval, in particular to a cross-media efficient indexing method based on massive data. Background technique [0002] With the rapid development of Internet technology and the popularity of social networks, the amount of multimedia data on the network is growing at an alarming rate. Multimedia data has complex semantics and is difficult to measure directly. The general method is to perform feature extraction on it to obtain corresponding features. Usually these features are high-dimensional, so the multimedia data retrieval problem is transformed into a high-dimensional data retrieval problem. The time complexity of the traditional brute force linear comparison strategy obviously cannot meet the online search needs of users in the face of large-scale high-dimensional data. At this time, people need an effective indexing mechanism to achieve efficient retrieval of high-dimensional data. Hash method is a hot res...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/30
Inventor 吴飞张寅余宙邵健庄越挺
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap