Many cloud vision APIs are available on the internet to recognize emotion from facial images and video analysis. The capacity to recognize emotions under various poses is a fundamental requirement in the area of emotion recognition. In this paper, the performance of two famous emotion recognition APIs is evaluated under the facial images of various poses. The experiments were done with the public dataset containing 980 images of each type of five poses [full left, half-left, straight, half-right, and full-right] with the seven emotions (Anger, Afraid, Disgust, Happiness, Neutral, Sadness, Surprise). It has been discovered that overall recognition accuracy is best in Microsoft Azure for straight images, whereas the face detection capability is better in Google. The Microsoft did not detect almost any of the images with full left and full right profile, but Google detected almost all of them. The Microsoft API presents an average true positive value up to 60%, whereas Google presents the maximum true positive value 45.25%.
