Parametric Prediction of Optical Tracker using Machine Learning Techniques for an efficient Head Tracking
Aman Kataria1, Smarajit Ghosh2, Vinod Karar3

1Aman Kataria*, Research Scholar, Thapar Institute of Engineering andTechnology, Patiala, India.
2Smarajit Ghosh, Professor, Thapar Institute of Engineering and Chief Scientist, CSIR-CSIO, Chandigarh Technology, Patiala, India.
3Vinod Karar, Chief Scientist, CSIR-CSIO, Chandigarh, India.

Manuscript received on 6 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 3045-3050 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4860098319/2019©BEIESP | DOI: 10.35940/ijrte.C4860.098319
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Abstract: A head tracker is a crucial part of the head-mounted display systems, as it tracks the head of the pilot in the plane/cockpit simulator. The operational flaws of head trackers are also dependent on different environmental conditions like different lighting conditions and stray light interference. In this paper, an optical tracker has been employed to gather the 6-DoF data of head movements under different environmental conditions. Also, the effect of different environmental conditions and variation in distance between the receiver and optical transmitter on the 6-DoF data is analyzed. This can help in the prediction of the accuracy of a optical head tracker under different environmental conditions prior to its deployment in the aircraft.
Keywords: Machine Learning, Head Tracking, Random Forest, Optical Head Tracking, Aviation

Scope of the Article:
Regression and Prediction