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Spatio-Temporal Wardrobe Generation of Actors’ Clothing in Video Content

  • Florian Vandecasteele
  • Jeroen Vervaeke
  • Baptist Vandersmissen
  • Michel De Wachter
  • Steven VerstocktEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9733)

Abstract

In this paper, we propose a methodology for spatio-temporal wardrobe generation for video content. The main goal is to suggest relevant matches between clothes worn by actors and images originating from a set of e-commerce clothing sites. The semi-automatic generation of fine-grained spatial metadata for each video sequence is based on shot detection, keyframe detection, feature matching and clothing type classification based filtering. The result of this annotation process is a spatio-temporal database consisting of videos and the corresponding actor clothing. This database can be queried in various ways depending on the intended target application.

Keywords

Video summarization Shot detection Clothing annotation Metadata enrichment Deep learning 

Notes

Acknowledgments

SpotShop (http://www.iminds.be/nl/projecten/2015/10/01/ spotshop) is a research project facilitated by iMinds and funded by the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Florian Vandecasteele
    • 1
  • Jeroen Vervaeke
    • 1
  • Baptist Vandersmissen
    • 1
  • Michel De Wachter
    • 2
  • Steven Verstockt
    • 1
    Email author
  1. 1.ELIS Department - Data Science LabGhent University IMindsGhentBelgium
  2. 2.AppinnessAalstBelgium

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