Visual pattern discovery for architecture image classification and product image search

Wei Ta Chu, Ming Hung Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

45 Citations (Scopus)

Abstract

Many objects have repetitive elements, and finding repetitive patterns facilitates object recognition and numerous applications. We devise a representation to describe configurations of repetitive elements. By modeling spatial configurations, visual patterns are more discriminative than local features, and are able to tackle with object scaling, rotation, and deformation. We transfer the pattern discovery problem into finding frequent subgraphs from a graph, and exploit a graph mining algorithm to solve this problem. Visual patterns are then exploited in architecture image classification and product image retrieval, based on the idea that visual pattern can describe elements conveying architecture styles and emblematic motifs of brands. Experimental results show that our pattern discovery approach has promising performance and is superior to the conventional bag-of-words approach.

Original languageEnglish
Title of host publicationProceedings of the 2nd ACM International Conference on Multimedia Retrieval, ICMR 2012
DOIs
Publication statusPublished - 2012
Event2nd ACM International Conference on Multimedia Retrieval, ICMR 2012 - Hong Kong, China
Duration: 2012 Jun 52012 Jun 8

Publication series

NameProceedings of the 2nd ACM International Conference on Multimedia Retrieval, ICMR 2012

Conference

Conference2nd ACM International Conference on Multimedia Retrieval, ICMR 2012
Country/TerritoryChina
CityHong Kong
Period12-06-0512-06-08

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software

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