Cleaning up after a face tracker: False positive removal

Makarand Tapaswi, Cemal Çaʇi Çörez, Martin Bäuml, Hazim Kemal Ekenel, Rainer Stiefelhagen

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

Abstract

Automatic person identification in TV series has gained popularity over the years. While most of the works rely on using face-based recognition, errors during tracking such as false positive face tracks are typically ignored. We propose a variety of methods to remove false positive face tracks and categorize the methods into confidence- and context-based. We evaluate our methods on a large TV series data set and show that up to 75% of the false positive face tracks are removed at the cost of 3.6% true positive tracks. We further show that the proposed method is general and applicable to other detectors or trackers.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages253-257
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - Jan 28 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • face tracking
  • false positive removal
  • TV series
  • video processing

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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