Visual Attribute Extraction Using Human Pose Estimation

  • Angelo Nodari
  • Marco Vanetti
  • Ignazio Gallo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7887)

Abstract

We propose a method to describe how a person is dressed, using an innovative way to extract Visual Information exploiting the Human Pose Estimation. Given the lack of algorithms in this field, we aims to pave the way giving a baseline and publishing a detailed dataset for future comparisons. In particular in this study we show how using the Human Pose Estimation, we are able to extract the essential features for the description of the Visual Attributes. Furthermore, the proposed method is able to manage the problems highlighted in literature regarding the extraction of features from images of people due to their articulated poses. For this reason we also propose a formalization of how describe people’s clothing in order to give a starting point and facilitate the analysis and the Visual Attributes extraction phase. Moreover we show how the use of Deformable Structures let us to extract Visual Attributes without the using of segmentation algorithms.

Keywords

Clothing Parsing Visual Attributes Human Pose Estimation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Angelo Nodari
    • 1
  • Marco Vanetti
    • 1
  • Ignazio Gallo
    • 1
  1. 1.Dipartimento di Scienze Teoriche e ApplicateUniversità dell’InsubriaVareseItaly

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