In this paper, we present a comparison of the accuracies of AI-based object recognition using a general camera and an omnidirectional camera. Recently, with the improvement in machine learning technology, there has been significant research related to the detection and classification of objects from images and videos. In this field, it is common to use horizontal images and videos. However, omnidirectional cameras, which can acquire information from the entire surrounding area, are becoming popular in addition to general cameras. Although there are some studies on object recognition using these cameras, almost no studies have focused on comparisons between object recognition using general and omnidirectional cameras. Therefore, in this study, we compared the recognition rate of object recognition using the YOLO algorithm on both general and omnidirectional images taken in the same environment.