Consider applications with artificial intelligence to augment a VR performance. We moved on to another motion capture technique after reaching this result, but the jury is still out on whether Mocha would be a completely useless solution for Oscillations’ purposes. This was the software we initially used to attempt a prototype with spatialized audio, and while we could visually fake spatialization we could not spatialize audio without Z-axis information. This is a limitation especially if Oscillations were to incorporate depth into their virtual reality experiences. However, right off the bat we noticed how tracking a 360 video is still just motion tracking in two dimensions.

Ranging from $995 to $1695, this option is on the relatively cheap side of motion capture technology and benefits from the fact that, except for a computer, Mocha does not need any additional hardware to work. The company has a VR (which they really mean 360) version that works specifically with equirectangular footage. Mocha is a graphic tracking software by Boris FX known for its planar tracking capabilities.

Our experiments are by no means scientifically sound nor rigorous, but we hope to give readers an intuition of each technology’s efficacy and even how to improve upon them for motion capture purposes. Each description is formatted similarly to a tech review you would see online and at the end, we summarize our findings in a chart. Apart from using ambisonic recordings, we attempted to sharpen the effect of audio-visual synchrony by connecting sounds to movements in post-production, but this proved to be difficult using only two-dimensional motion tracking software.Īlthough we did not have time to return to our spatial audio prototype with 3D data, below we describe the results of having played with five different hardware and software options for motion capture. With Oscillations’ connection to the movement arts, it made sense to experiment with existing motion capture technology to find accurate, consistent, and scalable ways to obtain three-dimensional motion data for purposes such as animation or machine learning to augment performances in virtual reality.Īn additional motivation to learn more about motion capture was connected to our early experiments with spatial audio (read more about them in our spatial audio blog post).

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