Thursday, March 2, 2017

33 Point Model! Thursday March 3rd, 2017

This week I had a chance to work with the 33 point model which was a huge step up from the 6 point model. The detail achieved with this model was incredible, but it came with its own slew of problems. Starting from the beginning, we first struggled with identifying where all the markers would go. We ended up with seven markers on each arm, six on each leg, four on the chest, and three on the head. The frustrating part was the double sided tape wasn't sticking very well to the suit, so after we decided where to put all the markers they kept falling off. Sort of like trying to keep two dogs in a bath tub, except there were 33 of them. Next, identifying markers in the system became a lot more difficult, like an intense game of connect the dots. Unfortunately, because of the cameras were positioned, it was hard to have all the markers show up during the capture. If one of the markers was missing, it wouldn't become apparent until the capture was completed. This meant it took us at least four or five attempts at subject prep to identify all the markers. Once this was completed, we were able to perform a capture. The majority of our time was then spent making sure all the markers were properly labelled and there were no gaps in the data. This happens with the six point model, so I was more familiar with this. We only did one lift, the squat lift, with this model because of the number of other problems that we encountered. 


1 comment:

  1. Now you have a thorough understanding of the capabilities of the motion measurement system. Remember that this system is used for character generation in movies and video games, as well. Those applications need 90-ppoint models and 3 times the number of cameras that we use.

    Anyway, you're now ready to start learning the nalytical methods that we use on the data from this system

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