MPM307 – Assignment #2: Documentation of Interactive Hat Experience

Group Members: Simone Roth , Kelly Truong, Jeffrey Leung

For this project, we couldn’t decide on an idea so we decided to fuse aspects of each of our proof of concepts together. Hats from mine, falling snow from Simone’s, and split screen from Kelly’s. Since we are not experts with processing and its integration with kinect motion detection, we didn’t want to do something that was too hard for us to handle.

^Please watch in 720p HD

Thus, we created a fun interactive piece that places a hat on the subject’s head. We added a feature where every time the subject claps his / her hands, the hat changes randomly. With 14 different hats stored, the subject can browse through them and do funny poses accordingly.


Our code uses OpenNI and Kinect to detect the subject’s head and body. We used arrays to organized and displays the hats. If statements were used to determine what happens when the subject claps his or her hands together. Also, we used if statements to determine when the subject is on the left or right side of the screen to activate the snowfall. We made it so the snowflakes fall at a random speed and location so it is more realistic. Sometimes the subject’s skeleton when calibrated is a bit off to the side, and sometimes it’s spot on. We don’t know why there is such inconsistency with the outcome, but we tried to adjust the positioning of the hat accordingly so it will somewhat fit properly on the subject’s head.


We had the idea to do only do winter themed hats which will go well with snowflakes falling, but we found that there are very limited amount of winter-hats. Since we already created the code for the falling snowflakes, we wanted to keep it but only activate the snow when the subject is on one side of the screen.

DSCF144123 We wanted to do something that is commercial, and that will appeal to the masses. We want our idea to be something you can see at a local store or mall, not specifically at an art gallery. At a grander scale, we would hope to have more than 50 different hats, and have alignment flawlessly executed every time.


We had a lot of fun creating this and will most definitely explore into Kinect in Processing for future projects.


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