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논문검색

Multi-modal Fusion Framework with Particle Filter for Speaker Tracking

초록

영어

In the domain of Human-Computer Interaction (HCI), the main focus of the computer is to interpret the external stimuli provided by users. Moreover in the multi-person scenar- ios, it is important to localize and track the speaker. To solve this issue, we introduce here a framework by which multi-modal sensory data can be eciently and meaningfully com- bined in the application of speaker tracking. This framework fuses together four dierent observation types taken from multi-modal sensors. The advantages of this fusion are that weak sensory data from either modality can be reinforced, and the presence of noise can be reduced. We propose a method of combining these modalities by employing a particle lter. This method oers satised real-time performance. We demonstrate results of a speaker localization in two- and three-person scenarios.

목차

Abstract
 1: Introduction
 2: The Proposed Approach
  2.1: Video Modality
  2.2: Audio Modality
  2.3: Particle Filter Implementation
 3: Experimental Results
 4: Conclusions and Future Work
 Acknowledgments
 References

저자정보

  • Anwar Saeed Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg
  • Ayoub Al-Hamadi Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg
  • Michael Heuer Institute for Electronics, Signal Processing and Communications (IESK) Otto-von-Guericke-University Magdeburg

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