OpenCV give us a native Matrix object that represents a frame in a video or live feed. We can easily extract an array of unsigned chars from it. In C++ unsigned char hold an integer value from 0 - 255. This number represents the luminosity of a colour or grayscale channel. 0 being complete black and 255 pure white. This is also the same range we use for front-end work with CSS attribute:function ( '''background-color: rgb(0, 191, 255)''' ). For the test below we use RGB or Red Green and Blue channels to calculate luminosity ourselves for more areas to optimize. However, for simplicity in explaining Algorthim in the next section, we are going to assume that OpenCV already gives us a greyscale frame, as it has ability to do so. This means that for a standard HD frame 1920 pixels by 1080 pixels we are given an array with 2,073,600 elements( unsigned char * data[2,073,600];)

This means that for a standard HD frame 1920 pixels by 1080 pixels we are given an array with 2,073,600 elements( unsigned char * data[2,073,600];) If we are processing a live feed at 30 frames per second we have a time constraint to process 62,208,000 elements (30 * 2,073,600) per second. From a perspective of a single frame, 1/30 that means have to process a frame under 33 millisecondsso as not to drop any frames.