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What is Retinad?
Retinad is a team of wide variety of experts, including neuroscientists, working on behavioral analytics of Virtual Reality content. That means tracking, measuring and trying tom ake sense of what a user does once they are in the headset. They are mainly focusing now on 360 videos.
Measurements implented already now include gaze tracking, *higher fannel analytics, such as google analytics, and more.
All in all, by recording where a user is looking, dynamics of VR can be derived, giving a sort of tree diagram when, where and what path a he or she chose.
At the moment, Retinad can be used as Unity plugin, providing data output through web dashboard. Additionally, it is compatible with Unreal Engine, Android, and GearVR.
Behavioral analytics approach
Can one capture the lougther using only an HMD? To validate this an other similar questions, behavioral data are compared to higher detail level data, such as EEG.
On the other hand, closer to the ground, what makes a 360 content a good one? On the one hand, this can be easily evaluated through so called Completion Rate - how many users did watch until the end? On the other hand, it is important to capture, how many users did look at the key components of the scene in the right time, such as main character performing an important part of the story - so basically evaluate how closesly did a user follow designed story board or workflow?
The fact is, it is hard to find a 360 video content that is compelling for anyone outside of VR community. That is why Retinad provides tools that help with creating the grammar of VR and 360 video content.
Thanks everyone for tuning in to another episode of ResearchVR. Hope you enjoyed listening to it and learned something new.
Thanks to Alexander Haque from Retinad for sharing his expertise with us and our listeners.
If you would like to hear more from Retinad, or use their tools, do not hesitate to contact them: firstname.lastname@example.org retinad.io
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Special thanks to Nerses Balabanian for the intro and outro music! Find him at here
38 episodes available. A new episode about every 12 days averaging 44 mins duration .