How to process videos using OpenCV

Video processing is manipulating and analyzing each video sequence frame to extract information or apply visual effects.

Video frames

Videos consist of a sequence of images that play one after the other. Hence, all the image processing methods can also be applied to individual video frames.

Note: Learn about the image processing and its implementation on the video frames.

Use cases

Using video processing, we can perform the following operations:

Object detection

Object detection is a computer vision task that involves locating and identifying objects of interest within an image or a video frame. This is typically done by drawing bounding boxes around the detected objects and labeling them with corresponding class labels.

Note: Learn about object detection in detail.

Object tracking

Video processing often involves tracking objects across frames. OpenCV provides algorithms for object tracking, allowing you to follow the movement of objects throughout a video. Unlike object detection, object tracking involves following the object throughout the video.

Note: Read about object tracking in depth.

3D face mesh

One of the finest applications of video processing is to detect the face and build a mesh over it. The mesh points out the eyes, nose, lips, and the boundaries of a human face.

Note: Learn how to implement a mesh over a face using OpenCV.

Conclusion

Image processing methods such as filtering, resizing, transforming, etc., can also be applied to the videos. Video processing techniques are primarily used for video editing in the entertainment industry. OpenCV's rich functionality and compatibility with different video sources make it a versatile tool for working with video data.

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