Computer Vision with MATLAB

Day 1 of 1

Importing, Visualizing, and Annotating Videos

Objective: Import videos into MATLAB, as well as annotate and visualize them. The focus is on using System Objects™ for performing iterative computations on video frames.

• Importing and displaying video files
• Highlighting objects by drawing markers and shapes like rectangles
• Combining and overlaying two images
• Performing iterative computations on video frames

Detecting Objects

Objective: Utilize machine learning and deep learning algorithms for complex object detection.

• Marking objects of interest in training images
• Training and using a cascade object detector
• Using a deep learning object detector

Estimating Motion

Objective: Estimate direction and strength of motion in a video sequence.

• Understanding motion perception in images
• Estimating motion using optical flow methods

Tracking Objects

Objective: Track single and multiple objects and estimate their trajectory. Handle occlusion by predicting object position.

• Tracking single objects using a Kalman Filter
• Tracking multiple objects using a GNN tracker

Camera Calibration

Objective: Remove lens distortion from images. Measure size of planar objects.

• Estimating intrinsic, extrinsic, and lens distortion parameters of a camera
• Visualizing the calibration error
• Removing lens distortion
• Measuring planar objects in real-world units