Saliency Weighted Features for Person Re-identification

  • Niki Martinel
  • Christian Micheloni
  • Gian Luca Foresti
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8927)

Abstract

In this work we propose a novel person re-identification approach. The solution, inspired by human gazing capabilities, wants to identify the salient regions of a given person. Such regions are used as a weighting tool in the image feature extraction process. Then, such novel representation is combined with a set of other visual features in a pairwise-based multiple metric learning framework. Finally, the learned metrics are fused to get the distance between image pairs and to re-identify a person. The proposed method is evaluated on three different benchmark datasets and compared with best state-of-the-art approaches to show its overall superior performance.

Keywords

Local Binary Pattern Salient Region Saliency Detection Local Binary Pattern Feature Camera Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Niki Martinel
    • 1
  • Christian Micheloni
    • 1
  • Gian Luca Foresti
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of UdineUdineItaly

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