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  • 标题:Hybrid Head Tracking for Wheelchair Control Using Haar Cascade Classifier and KCF Tracker
  • 本地全文:下载
  • 作者:Fitri Utaminingrum ; Yuita Arum Sari ; Putra Pandu Adikara
  • 期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
  • 印刷版ISSN:2302-9293
  • 出版年度:2018
  • 卷号:16
  • 期号:4
  • 页码:1616-1624
  • DOI:10.12928/telkomnika.v16i4.6595
  • 语种:English
  • 出版社:Universitas Ahmad Dahlan
  • 其他摘要:Disability may limit someone to move freely, especially when the severity of the disability is high. In order to help disabled people control their wheelchair, head movement-based control is preferred due to its reliability. This paper proposed a head direction detector framework which can be applied to wheelchair control. First, face and nose were detected from a video frame using Haar cascade classfier. Then, the detected bounding boxes were used to initialize Kernelized Correlation Filters tracker. Direction of a head was determined by relative position of the nose to the face, extracted from tracker’s bounding boxes. Results show that the method effectively detect head direction indicated by 82% accuracy and very low detection or tracking failure.
  • 关键词:head;detecting;tracking
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