Indonesian Lecturer Innovates Face Recognition Using Microexpression

TEMPO.CO, Jember - Indonesian lecturer from the Faculty of Technology at the University of Jember, Ike Febriani, is innovating in face recognition through microexpressions. Her research endeavors to identify family relationships or Kinship Recognition using two advanced technologies, Vision Transformer (ViT) and Mamba, with a hybrid model system called VitMa.

"My research focuses on identifying family relationships (Kinship Recognition) through microexpressions on the faces of Indonesians," said Ike in her written statement on Tuesday, April 8, 2025.

Ike is developing a new model that combines two advanced technologies, ViT and Mamba. This hybrid model aims to improve the accuracy in recognizing family relationships, which was previously a major challenge in facial recognition research, with no previous research on the correlation between kinship and microexpressions.

This lecturer in the Electrical Engineering undergraduate and graduate programs explains the reasons for choosing this research. "I think this research can be considered the first in the world because there is no research that discusses the relationship between kinship and microexpressions," said Ike, who also teaches at the Vocational Campus of UNEJ.

Ike stated that the combination of the two advanced technologies, ViT and Mamba, which is then named VitMa, in a single hybrid model for kinship recognition has never been done before. "This combination effectively enables the detection of very subtle facial expressions," she added.

According to Ike, this research stemmed from her interest in developing facial recognition technology and its application in family relationships. She then evolved her research to focus on recognizing family relationships through a microexpression approach.

"To improve the accuracy in recognizing family relationships, and to contribute to the development of facial recognition technology that is more sensitive to local cultural contexts," she added.

Ike continues to develop this research. "The main innovation that I will make to this research is to improve the model's ability to detect microexpressions with higher accuracy, expand the data sets used, integrate this model with voice recognition technology or text analysis, and develop broader practical applications," she said.

To motivate her students, Ike said, "Students must be innovative amidst the rapid development of technology; they must be able to follow the latest technological advancements and actively collaborate across disciplines or with professionals from other fields of study."

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