Arrived to the post production phase.
First of all, I tried to stretch the movie, in order to arrive to 3 minutes which I thought it was the duration the film had to have. I included a lot of walking, too much walking, it made it pretty boring and not interesting, the focus was even shifting from the actual facial recognition process to people blankly walking in the street.
However, reading again the brief, I figured out that 3min was only the maximum duration of the movie, so I cut the walking scenes arriving to a length of about 2 minutes.
After cutting roughly the scenes I picked a song to use as background, it took me a while to decide the right one for this sort of video, but finally the choice fell on one of my favourite artists, Paul Kalkbrenner. Besides the personal preference I think that Kalkbrenner’s minimal music fits perfectly for this sort of footage, cold, deep and detached.
Regarding the boxes on the which information of the person are displayed, I kept them as simple as possible. I also tried an option a bit more detailed and graphically more pleasant, but the space started to look too crowded. Having only a bunch of seconds to express the idea, I needed these scenes to be as clear as possible, putting as much text as possible, but still leaving it easily readable.
For this reason I used the Typewriter effect to compose the text. It made easier the reading as the text appears letter by letter and the viewer eyes know exactly what to follow.
Furthermore, in order to fit more information as possible I used short names, such as Jan Feld. The actor (Pim), comes from the Netherlands, but obviously I couldn’t use his country as the name is too long. I firstly thought about Germany, but Austria is actually shorter and probably the easiest to read among Central Europe countries. Obviously Pim doesn’t look Spanish, otherwise “Vigo, Spain” would have done the trick. Same thought applied also to the other texts.
Finally, there is a detail which is not too explicit, the colour of the boxes: if the machine judge positively the target it’s green if negatively red, if not recognised black.
Tobias suggested to show this more clearly, I therefore tried using emoticons, thumbs up and down, but it looked cheesy and childish. The effect was to deviate the attention from the text, so I preferred to keep this colour distinction implicit.