Well, my master thesis was a while ago – still here some interesting insights about what I did. I cannot share much more information, but if you’re interested about the details, just send me an email and we can talk about it.
The major goal of advertisement is to target the users needs and wishes as best as possible. Online advertisement offers a whole new spectrum of information combination to target these of a single user as best as possible. If 3D body scans of users and customers would be available, the targeting ratio of their needs could increase significantly by automatically identifying more personal aspects of this person – e.g. their exercised sport.
Using the morphable model concept for 3D models on professional athletes and normalizing the position allows predicting a person’s sport. It was determined, that the prediction accuracy is up to 73%. With this, sport gear companies can identify the exercised sport of each customer and provide the relevant and needed products. Therefore, research in this area should be extended, to improve and automate the prediction process much more in order to improve advertising and boost sales.
So what I did was taking a lot of 3D body scans and found out an automatic way in how to determine the sport of a person. So I used the morphable model, normalized positions and try to find clusters with the use of professional athletes of a single sport. In the end I tried to map testing persons to those clusters to see if the persons “fit” to the right sport.
I have to admin my geographical life is a little bit of a mess. I am travelling to our customer for about three days a workweek, love to visit friends all over in south Germany at the weekend and still have to visit my family in my hometown somewhere in between. So I would say I hit the road very often.
Google Now for Android loves to give you information about locations and how much time it takes to those locations. Places you visit a lot seem to appear in your Google Now cardset more often. Mostly they will tell you how long it takes to get there and how the traffic looks like. This intelligence is a part of the first smart devices today, which try to think ahead and give you the right information to the right time.
A while ago I read an article about a person who built his whole life on his smart home. He has a server room with millions of cables in his basement and tries to let his home think more than he does. The problem he faced was that this “smartness” after a while began to trample on his nerves, so he reduced the smartness more and more. Giving information about the weather when you leave your home seems like a great idea – but nobody likes to get this information every time. Really every time. Which leads about thinking that this “simple smartness” is still not smart enough, because it does not know any detail about you and your day. And this is where smart devices are critical. Being smart without annoying. In my case this led to traffic information about the way to my workplace – on the weekend.
Due to being at the customers place three days a week I live in the hotel those days. On my way home from the office today, Google Now asked me if I want to receive information about the way to this hotel and I had to decide between “Yes” and “No”, which seems to be an overly simple binary decision. The same issue appears on Amazons Fire TV. They will give you suggestions about which shows or movies you can watch, but you have always the option to remove specific shows or movies from these suggestions. This is probably because those applications want to improve suggestions for you. But also here are a lot of reasons why a user can remove this suggestion. I’ve already seen a lot of movies and 10 suggestions with 8 movies I’ve already seen make no sense for me. If I remove those now, what does my Fire TV think about it? I don’t like the movies and it will not suggest any movies like this? But if I do like those movies it will not improve those suggestions but make it worse. You’ll find different “like or not like” mechanics in all kind of websites and apps like Facebook, Youtube, Spotify, Netflix, etc.
Yet the question is if these simple questions really improve your user experience – and I dont think so.
tl;dr: If smart applications want to improve their smartness, it will not work with dumb questions.