scholarly journals Facial Expression Recognition and Analysis: A Comparison Study of Feature Descriptors

2015 ◽  
Vol 7 (0) ◽  
pp. 104-120 ◽  
Author(s):  
Chun Fui Liew ◽  
Takehisa Yairi
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Comparison Study ◽  
Feature Descriptors

scholarly journals Modified chess patterns: handcrafted feature descriptors for facial expression recognition

2021 ◽  
Author(s):  
Mukku Nisanth Kartheek ◽  
Munaga V. N. K. Prasad ◽  
Raju Bhukya
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Main Task ◽  
Expression Recognition ◽  
Distinctive Features ◽  
Symmetric Pattern ◽  
Feature Descriptors ◽  
Feature Values ◽  
Local Gradient

AbstractFacial expressions are predominantly important in the social interaction as they convey the personal emotions of an individual. The main task in Facial Expression Recognition (FER) systems is to develop feature descriptors that could effectively classify the facial expressions into various categories. In this work, towards extracting distinctive features, Radial Cross Pattern (RCP), Chess Symmetric Pattern (CSP) and Radial Cross Symmetric Pattern (RCSP) feature descriptors have been proposed and are implemented in a 5 $$\times $$ × 5 overlapping neighborhood to overcome some of the limitations of the existing methods such as Chess Pattern (CP), Local Gradient Coding (LGC) and its variants. In a 5 $$\times $$ × 5 neighborhood, the 24 pixels surrounding the center pixel are arranged into two groups, namely Radial Cross Pattern (RCP), which extracts two feature values by comparing 16 pixels with the center pixel and Chess Symmetric Pattern (CSP) extracts one feature value from the remaining 8 pixels. The experiments are conducted using RCP and CSP independently and also with their fusion RCSP using different weights, on a variety of facial expression datasets to demonstrate the efficiency of the proposed methods. The results obtained from the experimental analysis demonstrate the efficiency of the proposed methods.

Knight Tour Patterns: Novel Handcrafted Feature Descriptors for Facial Expression Recognition

2021 ◽  
pp. 210-219
Author(s):  
Mukku Nisanth Kartheek ◽  
Rapolu Madhuri ◽  
Munaga V. N. K. Prasad ◽  
Raju Bhukya
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Feature Descriptors
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