This example shows how to automatically determine the geometric transformation between a pair of images.
This example shows how to train an object detector using a deep learning technique named Faster R-CNN (Regions with Convolutional Neural Networks).
This example shows how to perform automatic detection and motion-based tracking of moving objects in a video from a stationary camera.
This example shows how to measure the diameter of coins in world units using a single calibrated camera.
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 how to combine multiple point clouds to reconstruct a 3-D scene using Iterative Closest Point (ICP) algorithm.
Learn the benefits and applications of local feature detection and extraction
Choose functions that return and accept points objects for several types of features
Interactively label rectangular ROIs for object detection, pixels for semantic segmentation, and scenes for image classification.
Estimate camera intrinsics, extrinsics, and lens distortion parameters.
Calibrate a stereo camera, which you can then use to recover depth from images.