Authors: Manish Sharma; Shikha N. Khera; Pritam Babu Sharma
Addresses: Delhi School of Management, Delhi Technological University, Bawana Road, Delhi-110042, India ' Delhi School of Management, Delhi Technological University, Bawana Road, Delhi-110042, India ' Vice Chancellor Office, Amity University Haryana, Manesar, Haryana-122413, India
Abstract: Emotional intelligence is to recognise emotions and emotions can be recognised by analysing face. Face reflects emotions, and thus facial images can help to identify emotions. Emotions recognition can help in conducting qualitative market research techniques like focus groups; in-depth interviews and other which can be used to generate customer intelligence. This paper provides a cross-disciplinary view of Intelligence. This paper proposes a machine learning-based model to accomplish the task of identifying emotions from given facial images. This paper uses a public database and divides the images into four groups. The feature extraction has been done by principal component analysis and the feature selection by fisher discriminant ratio. The classification has been done by support vector machine using k cross-validation. The accuracy, specificity and sensitivity are encouraging. The average accuracy is 0.84
Keywords: emotions; emotional intelligence; customer intelligence; support vector machine; SVM; principal component analysis; cross-validation; machine learning; artificial intelligence; qualitative market research techniques; focus groups; emotion recognition.
International Journal of Social Computing and Cyber-Physical Systems, 2019 Vol.2 No.2, pp.119 - 131
Received: 28 Jun 2018
Accepted: 14 Sep 2018
Published online: 14 Jun 2019 *