Extracting features from video frames

Another useful technique for the EDA of video data is to extract features from each frame and analyze them. Features are measurements or descriptors that capture some aspect of the image, such as color, texture, or shape. By analyzing these features, we can identify patterns and relationships in the data.

To extract features from each frame, we can use the OpenCV functions that compute various types of features, such as color histograms, texture descriptors, and shape measurements. Choosing the best feature extraction method depends on the characteristics of your data and the nature of the clustering task.

Let us see the color histogram feature extraction method.

Color histogram

A color histogram is a representation of the distribution of colors in an image. It shows the number of pixels that have different colors in each range of the color space. For example, a color histogram can show how many pixels are red, green, or blue in an...