139 citations · 147 across the 7 of their papers we have counts for
8 papers
Deep Insights of Learning based Micro Expression Recognition: A Perspective on Promises, Challenges and Research Needs
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh
Micro expression recognition (MER) is a very challenging area of research due to its intrinsic nature and fine-grained changes. In the literature, the problem of MER has been solve…
Cross-Centroid Ripple Pattern for Facial Expression Recognition
Monu Verma, Prafulla Saxena, Santosh Kumar Vipparthi +1
In this paper, we propose a new feature descriptor Cross-Centroid Ripple Pattern (CRIP) for facial expression recognition. CRIP encodes the transitional pattern of a facial express…
AffectiveNet: Affective-Motion Feature Learningfor Micro Expression Recognition
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh
Micro-expressions are hard to spot due to fleeting and involuntary moments of facial muscles. Interpretation of micro emotions from video clips is a challenging task. In this paper…
Non-Linearities Improve OrigiNet based on Active Imaging for Micro Expression Recognition
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh
Micro expression recognition (MER)is a very challenging task as the expression lives very short in nature and demands feature modeling with the involvement of both spatial and temp…
LEARNet Dynamic Imaging Network for Micro Expression Recognition
Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh +1
Unlike prevalent facial expressions, micro expressions have subtle, involuntary muscle movements which are short-lived in nature. These minute muscle movements reflect true emotion…
EXPERTNet Exigent Features Preservative Network for Facial Expression Recognition
Monu Verma, Jaspreet Kaur Bhui, Santosh Vipparthi +1
Facial expressions have essential cues to infer the humans state of mind, that conveys adequate information to understand individuals actual feelings. Thus, automatic facial expres…