Hybrid Head Tracking for Wheelchair Control Using Haar Cascade Classifier and KCF Tracker

Fitri Utaminingrum, Yuita Arum Sari, Putra Pandu Adikara, Dahnial Syauqy, Sigit Adinugroho


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.


head; detecting; tracking

Full Text:


DOI: http://dx.doi.org/10.12928/telkomnika.v16i4.6595

Article Metrics

Abstract view : 126 times
PDF - 32 times


  • There are currently no refbacks.

Copyright (c) 2018 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.