Part II - Motion Trails (using Edge-based Sharpening)

Explanation

Using the edge detection method previously, edges are detected on frames 1, 4 and 7 out of the collection of all frames, which is defaulted to 12. Each of these selected frames is then added onto the original video by adding up the RGB values. Since the edge detection algorithm only provides the edges and nothing else, the RGB components can be added directly without the need to edit alpha. The result is expected to show some sort of trails of the edges. This is achieved as seen below, reflected by the blue lines.

I'm afraid you'll need to click on the image to have a clearer view.

Question

1. If you used a video of people moving as a crowd, do you think it would be useful?

Yes, it will be useful. However, it may be computationally expensive as a lot of edges need to be calculated. Apart from that, the trails would be a very nice effect to have, visually.

Reflection 

Originally a headache to comprehend, the tutorials shed some light on the solution that I needed. Motion trails are basically just trails or outlines being displayed in a delayed manner. What I did was, I took the Laplacian algorithm as a function that returns the edges for a single frame. After gathering 12 frames, I process the first, fourth and seventh frame to get the edges that will form a trail. By now, you might've noticed that the video played is already 12 frames ahead. So what I thought I'd do is that, I'll just add these processed frames (with edges) onto the front canvas and repeat this until the video ends. Turns out I was right, and the above shows the result of my thought process.