The Indian Spontaneous Expression Database for Emotion Recognition

TL;DR

This paper introduces the Indian Spontaneous Expression Database, a new resource containing 428 video clips of genuine facial expressions from Indian participants, aimed at advancing spontaneous emotion recognition research.

Contribution

It presents a novel spontaneous facial expression database with detailed annotations, addressing the lack of such resources for Indian populations in affective computing.

Findings

Extensive analysis using machine learning algorithms on the database.

Validation of the database through stimuli and self-reports.

Provides a benchmark for future spontaneous expression recognition studies.

Abstract

Automatic recognition of spontaneous facial expressions is a major challenge in the field of affective computing. Head rotation, face pose, illumination variation, occlusion etc. are the attributes that increase the complexity of recognition of spontaneous expressions in practical applications. Effective recognition of expressions depends significantly on the quality of the database used. Most well-known facial expression databases consist of posed expressions. However, currently there is a huge demand for spontaneous expression databases for the pragmatic implementation of the facial expression recognition algorithms. In this paper, we propose and establish a new facial expression database containing spontaneous expressions of both male and female participants of Indian origin. The database consists of 428 segmented video clips of the spontaneous facial expressions of 50 participants. In our experiment, emotions were induced among the participants by using emotional videos and simultaneously their self-ratings were collected for each experienced emotion. Facial expression clips were annotated carefully by four trained decoders, which were further validated by the nature of stimuli used and self-report of emotions. An extensive analysis was carried out on the database using several machine learning algorithms and the results are provided for future reference. Such a spontaneous database will help in the development and validation of algorithms for recognition of spontaneous expressions.