Abstract
The main objective of this paper is to modify the facial features, to change the existing image based on description of height and width of the face components and to generate a transformed image. There are many challenges in dealing with the modification of existing face images which are variations in facial expressions can be a cause for confusion, lack of large-scale supervised datasets, both speed and scalability of system are of prime importance as results are expected in real times. The scope of the study is to test 30 male and female face images from ORL database. The study has been done using MATLAB R2013a .
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References
X. Wang, X. Tang, Face photo-sketch synthesis and recognition. IEEE Trans. Pattern Anal. Mach. Intell. 31(11), 1955–1967 (2009)
M. Leung, H.Y. Hui, I. King, Facial expression synthesis by radial basis function network and image warping, in IEEE International Conference on Neural Networks, vol. 3, pp. 1400–1405
D. Bhattacharjee, S. Halder, M. Nasipuri, D.K. Basu, M. Kundu, Construction of human faces from textual descriptions. Soft Comput. Fusion Found. Methodologies Appl. 15(3), 429–447 (2009). (Springer)
Bernard Tiddeman, Michael Burt, David Perrett, Prototyping and transforming facial textures for perception research. IEEE Comput. Graph. Appl. 21(5), 42–50 (2001)
Y.Y. Tang, C.Y. Suen, Image transformation approach to nonlinear shape restoration. IEEE Trans. Syst. Man Cybern. 23(1), 155–172 (1993)
F. Perronnin, J.-L. Dugelay, K. Rose, A probabilistic model for face transformation with application to person identification. EURASIP J. Appl. Sig. Process. 4, 510–521 (2004)
Y. Rui, T.S. Huang, Image retrieval: current techniques, promising directions, and open issues. J. Vis. Commun. Image Represent. 10, 39–62 (1999)
G. Bebis, M. Georgiopoulos, N. da Vitoria Lobo, M. Shah, Recognition by learning affine transformations. Pattern Recogn. 32(10), 1783–1799 (1999)
R.C. Gonzalez, P. Wintz, Digital Image Processing, 2nd edn. (Addison Wesley, Publisher, 1987)
OpenGL-ARB, OpenGL Reference Manual: The Official Reference Document to OpenGL, Version 1.1., 2nd edn. (Addison-Wesley, Reading, MA, 1997)
A. Watt, 3D Computer Graphics, 3rd edn. (Addison-Wesley, Reading, MA, 1995)
P. Kale, K.R. Singh, A technical analysis of image stitching algorithm. Int. J. Comput. Sci. Inf. Technol. 6(1), 284–288 (2015)
K. Shashank, N. SivaChaitanya, G. Manikanta, ChNV Balaji, V.V.S. Murthy, A survey and review over image alignment and stitching methods. Int. J. Electron. Commun. Technol. 5, 50–52 (2014)
R. Szeliski, Image alignment and stitching. Found. Trends Comput. Graph. Vis. 2(1), 1–104 (2006)
E. Adel, M. Elmogy, H. Elbakry, Image stitching based on feature extraction techniques: a survey. Int. J. Comput. Appl. 99(6), 1–8 (2014)
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Pal, M., Ghosh, S., Sarkar, R. (2020). Modification of Existing Face Images Based on Textual Description Through Local Geometrical Transformation. In: Mandal, J., Bhattacharya, D. (eds) Emerging Technology in Modelling and Graphics. Advances in Intelligent Systems and Computing, vol 937. Springer, Singapore. https://doi.org/10.1007/978-981-13-7403-6_16
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DOI: https://doi.org/10.1007/978-981-13-7403-6_16
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