Registering two images is a simple way to understand local features. This example finds a geometric transformation between two images. It uses local features to find well-localized anchor
Builds on the results of the "Use Local Features" example. Using more than one detector and descriptor pair enables you to combine and reinforce your results. Multiple pairs are also useful
Automatically determine the geometric transformation between a pair of images. When one image is distorted relative to another by rotation and scale, use detectSURFFeatures and
Combine multiple point clouds to reconstruct a 3-D scene using Iterative Closest Point (ICP) algorithm.
Structure from motion (SfM) is the process of estimating the 3-D structure of a scene from a set of 2-D images. This example shows you how to estimate the poses of a calibrated camera from two
Perform automatic detection and motion-based tracking of moving objects in a video from a stationary camera.
Train an object detector using a deep learning technique named Faster R-CNN (Regions with Convolutional Neural Networks).