2023/03/23 by Salik Ram Khanal, Khanal, Salik Ram, Prabin Sharma +7
Computer Science · Neuroscience · #Brain Tumor Detection and Classification #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition
paper · pdf · doi:10.48550/arxiv.2303.12974
openalex publication_date 2023/03/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Facial expression is a way of communication that can be used to interact with computers or other electronic devices and the recognition of emotion from faces is an emerging practice with application in many fields. There are many cloud-based vision application programming interfaces available that recognize emotion from facial images and video. In this article, the performances of two well-known APIs were compared using a public dataset of 980 images of facial emotions. For these experiments, a client program was developed which iterates over the image set, calls the cloud services, and caches the results of the emotion detection for each image. The performance was evaluated in each class of emotions using prediction accuracy. It has been found that the prediction accuracy for each emotion varies according to the cloud service being used. Similarly, each service provider presents a strong variation of performance according to the class being analyzed, as can be seen with more detail in this artilects.