Emotion Detection using Image Processing in Python
This work addresses the problem of emotion recognition from facial expressions for general computer vision applications, representing an incremental contribution to an existing field.
This paper presents a system developed in Python using OpenCV and NumPy to detect human emotions from facial expressions in live camera feeds or pre-existing images. The system compares scanned images against a training dataset to predict emotions.
In this work, user's emotion using its facial expressions will be detected. These expressions can be derived from the live feed via system's camera or any pre-exisiting image available in the memory. Emotions possessed by humans can be recognized and has a vast scope of study in the computer vision industry upon which several researches have already been done. The work has been implemented using Python (2.7, Open Source Computer Vision Library (OpenCV) and NumPy. The scanned image(testing dataset) is being compared to the training dataset and thus emotion is predicted. The objective of this paper is to develop a system which can analyze the image and predict the expression of the person. The study proves that this procedure is workable and produces valid results.