Project

Facial Expression Recognition

Research objective is to develop an artificially intelligent human behavioral assessment system to analyze emotions using visual data which can be easily collected through various sensory mediums. Our focus is to develop deep learning architecture suitable for detecting micro level information from the facial appearances.

PROJECTS

Non-Linearities Improve OrigiNet based on Active Imaging for Micro Expression Recognition

Paper PPT Source Codes

Micro Expression Recognition using LearNet

Paper PPT Source Codes

Facial Expression Recognition Using HiNet

Paper PPT

Facial Expression Recognition Using ExpertNet

Paper PPT

Facial Expression Recognition Using QUEST Discriptor

Paper PPT

Facial Expression Recognition Using ReTrain Discriptor

Paper PPT

Related Publication

1. Monu Verma, Santosh Kumar Vipparthi, Girdhari singh, “Non-Linearities Improve OrigiNet based on Active Imaging for Micro Expression Recognition,” IEEE International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom, 2020.

2. Monu Verma, Prafulla saxena, Santosh Kumar Vipparthi, Girdhari Singh, S. K. Nagar, "DeFINet: PORTABLE CNN NETWORK FOR FACIAL EXPRESSION RECOGNITION," IEEE International Conference on Information and Communication Technology for Competitive Strategies, Udaipur, INDIA, 2019.

3. Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh, Subrahmanyam Murala, “LEARNet: Dynamic Imaging Network for Micro Expression Recognition,” IEEE Transactions on image processing, 2019(IF 6.79).

4.Murari Mandal, Monu Verma, Sonakshi Mathur, Santosh Kumar Vipparthi, Subrahmanyam Murala, Kranthi Kumar Devarasetti, “RADAP: Regional Adaptive Affinitive Pattern with Logical Operators for Facial Expression Recognition,” IET Image Processing, 2019(IF 2.004).

5. Monu Verma, Santosh Kumar Vipprathi, Girdhari Singh, "HiNet: Hybrid Inherited Feature Learning Network for Facial Expression Recognition ," IEEE Letters of the Computer Society , 2019.

6.Monu Verma, Jaspreet Singh, Santosh Kumar Vipparthi, Girdhari Singh, “EXPERTNet: Exigent Features Preservative Network for Facial Expression Recognition,” 11th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2019.

7.Monu Verma, Prafulla Saxena, Santosh Kumar Vipparthi, Girdhari Singh, “QUEST: Quadrilateral Senary bit Pattern for Facial Expression Recognition,” In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1498-1503, 2019.

8. Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh, “Region Based Extensive Response Index Pattern for Facial Expression Recognition,” In 2018 International Conference on Communication, Computing and Internet of Things (IC3IoT), pp. 20-24, 2018.