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Facial Expression Recognition using Save and Load Keywords

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Niranjan Bhattacharyya, Anshul Sharma

Niranjan Bhattacharyya and Anshul Sharma. Facial Expression Recognition using Save and Load Keywords. International Journal of Computer Applications 155(6):42-44, December 2016. BibTeX

	author = {Niranjan Bhattacharyya and Anshul Sharma},
	title = {Facial Expression Recognition using Save and Load Keywords},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {155},
	number = {6},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {42-44},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2016912335},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Human expression is one of the most used gesture to express and understand the true intentions of a person. Recognition of human facial expression can be very useful in lie detection. It is mainly used for security reasons so that human behavior can be determined more efficiently, which is difficult for a human eye to detect. This paper focusses on the problem of facial expression recognition and suggests how to make it more efficient and faster. Facial expression code usually takes very long time to load all the database images to which current images can be matched. This problem will be solved by using ‘Save’ [1] and ‘Load’ [8] keywords in the Matlab code for expression recognition. Findings have shown that the code execution was around seventeen percent faster with the use of ‘Save’ and ‘Load’ keywords.


  1. Save keyword description by Mathworks,
  2. Journal on Facial Expressions Analysis by Ying-Li Tian, Takeo Kanade, and Jeffrey F. Cohn.
  3. M. Turk and A. Pentlnd, “Eigenfaces for Recognition,” J. CognotiveNueroscience, vol.3, no.1 pp. 71-86, 1991.
  4. Lindsay I Smith. “A Tutorial on Principal Component Analysis”.
  5. Facial Expression Recognition using PCA by DebasmitaChakrabarti and Debtanu Dutta.
  6. Save, Load and Delete Workspace Variable by Mathworks,
  7. Difference between .m and .mat file by Andreas Goser,
  8. Load keyword description by Mathworks,
  9. Recognizing Facial Expressions with PCA and ICA onto dimension of the emotion by Young-suk Shin.
  10. Recognizing faces with PCA and ICA by Bruce A.Draper, KyungimBaek, Marian Stewart Barlett and J. Ross Beveridge.
  11. The Universally Recognized Facial Expressions of Emotions by Cole Calistra.


.mat, Facial Expression Recognition, Load, Principal Component Analysis, Save.