Predicting Mouse Cursor Target using Backpropagation Neural Network
Pradeep V1, Jogesh Motwani2
1Pradeep V*, Research Scholar, Department of CSE, Channabasaveshwara Institute of Technology, Tumkur, India. Visvesvaraya Technological University, Belagavi, India.
2Jogesh Motwani, Professor, Department of CSE, Channabasaveshwara Institute of Technology, Tumkur, India. Visvesvaraya Technological University, Belagavi, India.
Manuscript received on January 11, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 2304-2309 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1787029420 /2020©BEIESP | DOI: 10.35940/ijitee.D1787.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Many solutions were proposed in the past decades to assist the people with disability in the movement to interact with personal computers. Various results were proposed to simulate the mouse cursor movement and click operations through facial expressions captured by the camera. Tracking and converting accurately the facial expression of the user to the mouse operation is still acknowledged as a research challenge and opportunity. The proposed system introduces a prediction of items to be selected by the user in the GUI based system applying the backpropagation neural network techniques to improve the performance of the overall selection process.
Keywords: Assistive Technology, Backpropagation Neural Network, Camera Mouse, Hands-free Computing, People with Disability, Predicting Mouse Cursor Target
Scope of the Article: Autonomic computing