Optical flow for motion estimation in video
Optical flow is the distribution of the apparent velocities of objects in an image. By estimating optical flow between video frames, you can measure the velocities of objects in the video. In general, moving objects that are closer to the camera will display more apparent motion than distant objects that are moving at the same speed.
Optical flow estimation is used in computer vision to characterize and quantify the motion of objects in a video stream, often for motion-based object detection and tracking systems.
For more information, see Computer Vision Toolbox, which supports common techniques such as the Horn-Schunk method and Lucas-Kanade algorithm. For additional techniques, see downloads in the MATLAB user community.
Examples and How To
- Object Detection, Motion Estimation, and Tracking (Documentation)
- Estimate Object Velocities (System Object)
- Optical Flow (Simulink Block)
- Motion Estimation by Block Matching (Simulink Block)
See also: object detection, object tracking, image stabilization, image processing and computer vision, image recognition, object recognition, digital image processing, feature matching, feature extraction, ransac, point cloud