Automatic Detection of Incorrect Location Images Uploaded by Users

Hsu Yung Cheng, Chih Chang Yu, Hsiang Yuan Liu, Sih Ying Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a system to automatically perform classification and data cleaning on location images in a database contributed by arbitrary users. Since human inspection is not feasible for large-scale databases, the ability to detect incorrect scenes uploaded by users is very important to maintain the correctness of the database. In this work, we compare different feature extractors using deep convolutional networks trained by massive datasets. Also, a detector is designed to identify incorrect scenes that can overcome the challenges of large intra-cluster distances. The experiments have validated the effectiveness of the proposed approach on a very challenging dataset.

Original languageEnglish
Title of host publicationIEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728118178
DOIs
StatePublished - Sep 2019
Event21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019 - Kuala Lumpur, Malaysia
Duration: 27 Sep 201929 Sep 2019

Publication series

NameIEEE 21st International Workshop on Multimedia Signal Processing, MMSP 2019

Conference

Conference21st IEEE International Workshop on Multimedia Signal Processing, MMSP 2019
Country/TerritoryMalaysia
CityKuala Lumpur
Period27/09/1929/09/19

Keywords

  • automatic data cleaning
  • location image analysis

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