Integrating Face-ID into an Interactive Person-ID Learning System

Autor/innen

  • Stephan Könn
  • Hartwig Holzapfel
  • Hazim Kemal Ekenel
  • Alex Waibel

DOI:

https://doi.org/10.2390/biecoll-icvs2007-119

Schlagworte:

online video-based face recognition, confidence, DDC: 004 (Data processing, computer science, computer systems)

Abstract

Acquiring knowledge about persons is a key functionality for humanoid robots. By envisioning a robot that can provide personalized services the system needs to detect, recognize and memorize information about specific persons. To reach this goal we present an approach for extensible person identification based on visual processing, as one component of an interactive system able to interactively acquire information about persons. This paper describes an approach for face-ID recognition and identification over image sequences and its integration into the interactive system. We compare the approach of sequence hypotheses against results from single image hypotheses, and a standard approach and show improvements in both cases. We furthermore explore the usage of confidence scores to allow other system components to estimate the accuracy of face-ID hypotheses.

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Veröffentlicht

2007-12-31

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Rubrik

The 5th International Conference on Computer Vision Systems