Human Mood Identification (Data Recording System)

Neha Mahajan; Satish Chaurasiya; Neelam Kurhade; Surepalli Saandeep; Mayuri Wanwad

International Journal of Image Processing and Pattern Recognition

Human Mood Identification (Data Recording System)

Abstract

Researchers across a variety of fields are becoming more interested in a human-computer interface system for automatic facial emotion identification. In our project, an Automatic Facial Expression Recognition System (AFERS) which records emotion for physiological analysis has been proposed. The suggested process consists of four steps: Identifying every face in the frame is part of the first stage. We focus on each face and adjust it in such a way that even if the face is turned in a different direction it is still able to identify the person. In the second stage, we will make use of a deep face algorithm to detect the emotion of the person. Unique features of the faces are selected that can be used to differentiate people and compare them with the faces of people stored in our database to recognize a person. The recognition rate for this method is around 90–95%. In the third stage, we have our Attendance System which will record the emotion of the person after every 1 sec which can be used to understand the person psychologically. At our final stage, we have developed GUI using Tkinter for user interaction.

Full text

The full text of this article is available to subscribers.

On a subscribing campus you are let in by network address, with no login at all.

One-off purchase. Permanent access to this article, no account needed.

A year of online access to every article in International Journal of Image Processing and Pattern Recognition. Or choose several journals →

How to cite

Neha Mahajan, Satish Chaurasiya, Neelam Kurhade, Surepalli Saandeep, Mayuri Wanwad. Human Mood Identification (Data Recording System). International Journal of Image Processing and Pattern Recognition. 2022;8(1):15–19.

Download the citation:

Article details

Human Mood Identification (Data Recording System)

Abstract

Read more of it

Publish your article

Abstract

Related articles

AI-Based Deepfake Voice Detection Model for Hindi Language

DEVELOPING A DRIVER DROWSINESS DETECTION SYSTEM (DDDS)

A Study on CNN-Based Image Mosaicing

Advanced Classification of Diabetic Retinopathy Using GAN and Deep Residual CNN Model

Vani-Adapt: A Zero-Shot Accent Trans-Adaptation Framework for Robust Indic Speech Recognition

Enhancing Facial Expression Analysis Using CNNs: Insights from ML and Deep Learning Comparisons

Read more of it

Publish your article