Abstract
Technological innovations draw the attention of all people, but not for those with motor disabilities as the contact with devices and such users draw on a line of frustration. One of the major problems faced by them is that they are unable to have full mouse access, the device which plays a major role in human–computer interaction. Several solutions have been made to address this issue, but they have limitations like using external devices like sensors which may not be affordable to all and require high-end computing because of the processing of data generated by external devices. To overcome this, a system is proposed for hands-free mouse control using facial gesture recognition techniques that can benefit people with motor disabilities. The proposed system intends to eliminate the use of external equipment and also simplify the interface for the disabled which was the major drawback in most of the existing systems. It makes use of face recognition and eye gestures by using only a webcam and uses this for mouse operations which makes the system much more cost effective and simpler. The proposed system uses a face detection algorithm using Histogram of Oriented Gradients (HOG) and was trained using the iBUG 300-W dataset which made the system a suitable solution for all lighting and environmental conditions. The evaluation of experimental performance indicates that the proposed system has extensive performance and never compromises in terms of stability and sensitivity.
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Anantha Prabha, P., Srinivash, K., Vigneshwar, S., Viswa, E. (2022). Mouse Assistance for Motor-Disabled People Using Computer Vision. In: Mahapatra, R.P., Peddoju, S.K., Roy, S., Parwekar, P., Goel, L. (eds) Proceedings of International Conference on Recent Trends in Computing . Lecture Notes in Networks and Systems, vol 341. Springer, Singapore. https://doi.org/10.1007/978-981-16-7118-0_35
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DOI: https://doi.org/10.1007/978-981-16-7118-0_35
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