A Kronecker Product Model for Repeated Pattern Detection on 2D Urban Images

Juan Liu, Emmanouil Z. Psarakis, Yang Feng, Ioannis Stamos

Research output: Contribution to journalArticle

Abstract

Repeated patterns (such as windows, balconies, and doors) are prominent and significant features in urban scenes. Therefore, detection of these repeated patterns becomes very important for city scene analysis. This paper attacks the problem of repeated pattern detection in a precise, efficient and automatic way, by combining traditional feature extraction with a Kronecker product based low-rank model. We introduced novel algorithms that extract repeated patterns from rectified images with solid theoretical support. Our method is tailored for 2D images of building façades and tested on a large set of façade images.

Original languageEnglish (US)
Pages (from-to)2266-2272
Number of pages7
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume41
Issue number9
DOIs
Publication statusPublished - Sep 1 2019

    Fingerprint

Keywords

  • Kronecker product model
  • low-rank
  • Repeated pattern detection
  • urban façade

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

Cite this