#faceware analyzer

This week we weren't in The Void, we were in the computer labs in order to utilise the Faceware Analyser and learn retargetting in Maya. We took the footage from last week and imported it into the Faceware Analyser software.

Here in the software, we were tasked with keyframing the largest points of difference so the software is able to track the movements in-between these frames. There is a full facial track mode but Jason suggested doing the elements of the face individually for a more accurate tracking. This was divided into the eyebrows, the eyes and the mouth. This is where the marks were significant because it corresponds to the points in the program. You essentially just line the points up with the dots for several keyframes.

The trick is to not create too many keyframes as it can cause the track to become very rigid and jerky. After the keyframes are created the program can then autotrack from those keyframes. This is then exported to Maya where we can see the Metahuman facial and body rigs. Unfortunately, this we where we ran into a lot of problems! For Natalie's rig the Metahuman's model imported strangely, it seemed like the arms and legs were attached to a different body type than the torso so theyimported in as collapsed shapes.

This was really strange but it didn't conflict with the facial rig, which was the main focus. However, attempting to use the facial rig did not work. The rig didn't seems connected to the model, so moving the eyes and the mouth was not possible. This was an issue across all the models, so we ended up having to troubleshoot in The Void. It became evident that transfering the files from the computer in The Void to the computer lab caused an error in the file directory which caused the rig to break. We were unable to get the facial rigs to work in the end.

This week was essentially a lot of troubleshooting, the Faceware Analyser keyframes were quite simple and intuitive once it was finished but the issues came about with the Metahumans. It involved a lot of problem-solving as we contemplated what could have happened to the models during the file transfers. This was still a good learning experience as using this kind of tech involves a lot of trial and error and problem-solving.

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