"Nowadays people are more interested in searching the relevant images directly through search engines like Google, Yahoo or Bing, these image search engines have dedicated extensive research effort to the problem of keyword-based image retrieval. However, the most widely used keyword-based image search engine Google is reported to have a precision of only 39%. And all of these systems have limitation in creating sentence-based queries for images.
This thesis studies a practical image search scenario, where many people feel annoyed by using only keywords to find images for their ideas of speech or presentation through trial and error. This thesis proposes and realizes a sentence-based image search engine (SISE) that offers the option of querying images by sentence. Users can naturally create sentence-based queries simply by inputting one or several sentences to retrieve a list of images that match their ideas well.
The SISE relies on automatic concept detection and tagging techniques to provide support for searching visual content using sentence-based queries. The SISE gathered thousands of input sentences from TED talk, covering many areas like science, economy, politics, education and so on. The comprehensive evaluation of this system was focused on usability (perceived image usefulness) aspect. The final comprehensive precision has been reached 60.7%. The SISE is found to be able to retrieve matching images for a wide variety of topics, across different areas, and provide subjectively more useful results than keyword-based image search engines"--Abstract, page iii.
Fan, Jun, 1971-
Electrical and Computer Engineering
M.S. in Computer Engineering
Missouri University of Science and Technology
viii, 30 pages
© 2015 Weizhi Meng, All rights reserved.
Thesis - Open Access
Querying (Computer science) -- Design
Pattern recognition systems
Electronic OCLC #
Meng, Weizhi, "A sentence-based image search engine" (2015). Masters Theses. 7474.