Deep ArUco: AI/ML-based Real-Time Marker Pose Tracking

Machine learning is commonly used in varoius types of machine vision. Convolutional neural network (CNN) are models that can be trained in different lighting, colors, changes and motion blur. This study generates data containing images with ArUco markers to be detected in different real-world scenarios. Environments created to detect the markers in this study is different lighting, motion blur, rain drops, different contrasts and fog. The ArUco markers will be detected by an existing detection algorithm using machine learning and artificial intelligence.