Monocular Depth Estimation and Detection of Near Objects

The image obtained from the cameras is 2D, so we cannot know how far the object is on the image. In order to detect objects only at a certain distance in a camera system, we need to convert the 2D image into 3D. Depth estimation is used to estimate distances to objects. It is the perception of the 2D image as 3D. Although different methods are used to implement this, the method to be applied in this experiment is to detect depth perception with a single camera. After obtaining the depth map, the obtained image will be filtered by objects in the near distance, the distant image will be closed, a new image will be run with the object detection model and object detection will be performed. The desired result in this experiment is, for projects with a low budget, instead of using dual camera or LIDAR methods, it is to ensure that a robot can detect obstacles that will come in front of it with only one camera. As a result, 8 FPS was obtained by running two models on the embedded device, and the loss value was obtained as 0.342 in the inference test performed on the new image, where only close objects were taken after the depth estimation.