New technique improves AI ability to map 3D space with 2D cameras
Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.
Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.
Photos are two-dimensional (2D), but autonomous vehicles and other technologies have to navigate the three-dimensional (3D) world. Researchers have developed a new method to help artificial intelligence (AI) extract 3D information from 2D images, making cameras more useful tools for these emerging technologies.
The Naive Bayes algorithm is a simple but powerful technique for supervised machine learning. Its Gaussian variant is implemented in the OpenCV library. In this tutorial, you will learn how to apply OpenCV’s normal Bayes algorithm, first on a custom two-dimensional dataset and subsequently for segmenting an image. After…