Accession Number:

AD1011038

Title:

Large-Scale Partial-Duplicate Image Retrieval and Its Applications

Descriptive Note:

Technical Report,23 Jan 2012,22 Jan 2016

Corporate Author:

TEXAS STATE UNIV SAN MARCOS SAN MARCOS United States

Personal Author(s):

Report Date:

2016-04-23

Pagination or Media Count:

52.0

Abstract:

The explosive growth of Internet Media partial-duplicatesimilar images, 3D objects, 3D models, etc. sheds bright light on many promising applications in forensics, surveillance, 3D animation, mobile visual search, and 3D modelobject search. Compared with the general images, partial-duplicate images have some intrinsic properties such as high repeatability of local features, consistent local patch appearance, and stable spatial configuration. Compared with the general 2D objects, 3D modelsobjects consist of 3D data information typically a list of vertices and faces to represent 3D objects. However, these unique properties of partial-duplicate images and 3D models have not been well exploited to design effective and efficient search algorithms. Because of this, existing works for large-scale partial-duplicate image retrieval and 3D model retrieval suffer from two major problems low accuracy and low efficiency. These problems make them fall far below many applications requirement. This project has investigated many key problems in large-scale partial-duplicatesimilar image and 3D model retrieval feature descriptor problem, image representation problem, index strategy problem, feature quantization problem, image search results quality assessment problem, image search reranking problem, sketch-based 3D model retrieval problem, and related search problems and has proposed a series of effective and efficient approaches to solve them.

Subject Categories:

  • Operations Research
  • Computer Programming and Software
  • Cybernetics
  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE