In the previous section, we dealt with 2D object recognition using a 2D and 3D sensor. In this section, we will discuss 3D recognition. So what is 3D object recognition? In 3D object recognition, we take the 3D data or point cloud data of the surroundings and 3D model of the object. Then, we match the scene object with the trained model, and if there is a match found, the algorithm will mark the area of detection.
In real-world scenarios, 3D object recognition/detection is much better than 2D because in 3D detection, we use the complete information of the object, similar to human perception. But there are many challenges involved in this process too. Some of the main constrains are computational power and expensive sensors. We may need more expensive computers to process 3D information; also, the sensors for this purpose are costlier.
Some of the latest applications using 3D object detection and recognition are autonomous robots, especially self-driving...
