ISSN 2394-5125
 

Research Article 


Face Feature point detection using hybrid method

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya.

Abstract
A Facial Feature point analysis and face feature categorization is essentialprocedure in face recognition and facial emotion recognition. Facial emotion
recognition is utilized in security systems, government application, academic applications. Currently, facial emotion recognition system identifies
differentexpressions from face like happy, sad, disgust, neutral, angry, fear, surprise and contempt. This facial emotion recognition technique used for
hugesizeinformationcollectioncapturedbelow independent lightning conditionsand different emotions of face. The suggested facial emotion recognition
system exists hybridization of Histogram of Gradient (HOG), Local Binary Pattern (LBP), Gabor Wavelet feature (GFeature), and Discrete Cosine
Transform (DCT) for facial key point identification. Facial key points are extracted using this hybrid method. The proposed method uses the kaggle
dataset which has 3,386 sample images of 1,711 people having eight expression of each person with variation is facial emotions. Using this database, we
are extracting 157 feature points and we will extract some important features among them for further classification. The performance of feature point
detection is achieving good using this hybrid method.

Key words: Facial Expression, Feature Extraction, Key point detection, face recognition, Classification.


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Manisha M. Kasar
Articles by S.H. Patil
Articles by Debnath Bhattacharya
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. Face Feature point detection using hybrid method. JCR. 2020; 7(15): 369-378. doi:10.31838/jcr.07.15.52


Web Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. Face Feature point detection using hybrid method. http://www.jcreview.com/?mno=119767 [Access: June 29, 2020]. doi:10.31838/jcr.07.15.52


AMA (American Medical Association) Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. Face Feature point detection using hybrid method. JCR. 2020; 7(15): 369-378. doi:10.31838/jcr.07.15.52



Vancouver/ICMJE Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. Face Feature point detection using hybrid method. JCR. (2020), [cited June 29, 2020]; 7(15): 369-378. doi:10.31838/jcr.07.15.52



Harvard Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya (2020) Face Feature point detection using hybrid method. JCR, 7 (15), 369-378. doi:10.31838/jcr.07.15.52



Turabian Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. 2020. Face Feature point detection using hybrid method. Journal of Critical Reviews, 7 (15), 369-378. doi:10.31838/jcr.07.15.52



Chicago Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. "Face Feature point detection using hybrid method." Journal of Critical Reviews 7 (2020), 369-378. doi:10.31838/jcr.07.15.52



MLA (The Modern Language Association) Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya. "Face Feature point detection using hybrid method." Journal of Critical Reviews 7.15 (2020), 369-378. Print. doi:10.31838/jcr.07.15.52



APA (American Psychological Association) Style

Manisha M. Kasar, S.H. Patil, Debnath Bhattacharya (2020) Face Feature point detection using hybrid method. Journal of Critical Reviews, 7 (15), 369-378. doi:10.31838/jcr.07.15.52