Determining the Position of an Object in Three-Dimensional Space Using a Single Image with Computer Vision Methods

Determining the position of objects in three-dimensional space from two-dimensional images is a crucial task in computer vision. This paper proposes a novel method that accurately determines the position of an object using only a single image, reducing dependence on complex hardware and manual configuration. Our approach involves using a reference three-dimensional model of the object to generate training data and subsequently calculate its position in space. The method comprises several key steps: object detection in the image, keypoint detection, orientation determination, depth and scale calculation of the object and rendering the object in a three-dimensional scene. A distinctive feature of our approach is the automation of training data preparation, making it scalable and efficient for various objects and conditions. This method enhances the accuracy and convenience of object position determination, which can significantly impact fields such as robotics, autonomous vehicles and virtual reality.