Total views : 3575732
Face Morphing and Substitution for Aid of Autistic Children using Augmented Reality
Objectives: This paper aims at easy training of teacher or day care to a child affected by Autism Spectrum Disorder (ASD) using Face Morphing. The augmented reality with the face morphing provides the better solution for this problem. Method: The Face identification, Feature extraction based on the way points and morphing are illustrated with the live image. When mapping the pixels of source image on the targeted image, an intermediate image will be generated with image transition. Findings: The intermediate image will be tracked back again to the source image, so that over a period of time the targeted image will be the familiar one in the application, which helps the trainer and the child to interact without any sort of difficulty. Applications: The system can be automated by introducing the intelligence in face morphing and blending.
Augmented Reality, Face Morphing, Local Binary Pattern (LBP), Tracking and Waypoints Substitution (FTAS).
- Sigman M, Mundy P, Sherman T, Ungerer J. Social interactions of autistic, mentally retarded and normal children and their caregivers. Journal of Child Psychology and Psychiatry. 1986 Sep; 27(5):647–56.
- Colavita visual dominance effect [Internet]. [Cited 2015 Nov 04]. Available from: https://en.wikipedia.org/wiki/Colavita_visual_dominance_effect.
- Bai AZ, Alan F, Blackwell. Using augmented reality to elicit pretend play for children with autism. IEEE Transactions on Visualization and Computer Graphics. 2015 May; 21(5):598–610.
- Perez P, Gangnet M, Blake A. Poisson image editing. ACM Transactions on Graphics (TOG). 2003 Jul; 22(3):313–18.
- Schwerdt K, James L, Crowley C. Robust face tracking using color. Fourth IEEE International Conference on Automatic Face and Gesture Recognition; 2000 Mar. p. 90–5.
- Philip A, Tresadern T, Mircea C, Ionita I, Cootes TF. Real-time facial feature tracking on a mobile device. International Journal of Computer Vision. 2012 Feb; 96(3):280–9.
- Lanitis A, Christopher J, Taylor T, Cootes TF. Automatic face identification system using flexible appearance models. Image and Vision Computing. 1995 Jun; 13(5):393–401.
- Panchal JB, Shah KR, Sanghani NJ, Jhaveri RH. An implementation of enhanced image morphing algorithm using hybrid approach. International Journal of Computer Applications. 2013 Mar; 66(20):14–18.
- Rao GS, Manjusha B. Design face track to achieve an efficient and real-time tracking through detecting the movement of a target. WSN’S. International Journal of Research in Computer and Communication Technology. 2015 Oct; 4(10):840–3.
- Pighin F, Szeliski R, Salesin DH. Modeling and animating realistic faces from images. Internationa Journal of Computer Vision. 2002 Nov; 50(2):143–69.
- Deepa A, Sasipraba T. Challenging aspects for facial feature extraction and age estimation. Indian Journal of Science and Technology. 2016 Jan; 9(4):1–6.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.