3D Tracking in Virtual Reality

Notable arivis InViewR Tracking Capabilities:

Import, edit and proofread tracks from arivis Vision4D

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Manually create tracks
from scratch

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Use existing or automatically created segments as track points

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Virtual reality assisted Tracking

Proofreading tracking data and manually adjusting the results is very cumbersome on a 2D screen. Especially, when lots of objects are involved or tracks are very complicated. Using Virtual Reality, you can immerse yourself into the data and gain a detailed view onto your sample, that a 2D application cannot match. Entering the dataset and looking at objects and structures as they are surrounding you makes it easier to concentrate on a particular object of interest. With time control on your fingertips, you can always keep your eyes on the object as it moves through the specimen and follow it in space. We developed tools that allow you to add new or edit and delete existing tracks right where you see them - in the image. This makes proofreading tracks faster, easier and more precise than on a desktop.

Proofread and Edit Tracks

Our new Tracking Module enables you to import, visualize and edit 3D tracks. Imported Tracks can originate from any automatic analysis operation you create in arivis Vision4D and are visualized just as you know from our desktop software. With arivis InViewR, you now can interact with those tracks using your own hands. In Virtual Reality, you can cut, merge or prolong tracks if you are not satisfied with the result from the automatic tracking algorithm. This is especially convenient for images, where 2 objects are very close together, giving tracking algorithms a hard time to differentiate two separate objects.

 

Tracking in Virtual Reality. Image Courtesy: Judith Reichmann, Jan Ellenberg; EMBL Heidelberg

Manual de-novo tracking

Besides editing existing tracks, de-novo tracking is also possible. Simply point your hand to the 3D object you want to follow and press a button. The image will automatically jump to the next frame, where you can point at the object again. Of course, these tracks can also be handed over to arivis Vision4D, enabling you to analyze your result statistically and create meaningful data.

Computer assisted manual tracking

If you rely on automatic segmentation results but automatic tracking is not possible, we also have a solution for you. By separating the two tasks tracking and segmentation, you can now get to a result, too. Simply segment your image in arivis Vision4D (or an Open Source Program such as ImageJ or Phython) and just connect these segments afterwards to tracks in arivis InViewR. Like this, you have still access to object features along their path as well as accurate tracking results.

 

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