Systems and methods employing predictive overfilling for virtual reality

1. A method performed at a server, comprising:

receiving head tracking position information from a client device, the head tracking position information associated with a user at the client device;

predicting a future head position of the user at a scan-out time for displaying a virtual reality (VR) video frame,

wherein the VR video frame is displayed to the user via the client device;

determining an overfill factor based on an expected error in the predicted future head position of the user;

rendering an overfilled image based on the predicted future head position of the user and the overfill factor; and

sending the VR video frame comprising the overfilled image to the client device for display to the user,

wherein the expected error in the predicted future head position of the user is computed based on a latency distribution, the latency distribution comprising latency metrics data for multiple VR video frames previously scanned out for display by the client device.

2. The method of claim 1 , wherein the client device comprises a head-mounted display (HMD).

3. The method of claim 1 , wherein rendering the overfilled image further comprises:

determining at least two fields of view corresponding to at least two respective predicted future head positions of the user; and

rendering the overfilled image to comprise the at least two fields of view and content extended beyond the at least two fields of view based on the overfill factor.

4. The method of claim 1 , wherein at least one of pixel dimensions or an aspect ratio is changed dynamically from one VR video frame to another VR video frame according to a change in a head rotation of the user.

5. The method of claim 1 , wherein predicting the future head position of the user at the scan-out time comprises:

using at least in part the head tracking position information to predict the future head position of the user at the scan-out time.

6. The method of claim 5 , wherein using at least in part the head tracking position information to predict the future head position of the user at the scan-out time comprises:

predicting a first field of view (FOV) at a first time (T1),

wherein the first predicted FOV is based on a predicted first fixation point; and

predicting a second FOV at a second time (T2),

wherein the second predicted FOV is based on a predicted second fixation point.

7. The method of claim 6 , further comprising:

adding a first error margin associated with the predicted first fixation point to the first predicted FOV; and

adding a second error margin associated with the predicted second fixation point to the second predicted FOV.

8. The method of claim 7 , further comprising confirming values of the first and second error margins in real-time based on the head tracking position information received from the client device.

9. The method of claim 8 , wherein the first prediction error margin and the second prediction error margin are based on errors between the received head tracking position information and predicted motion data.

10. The method of claim 7 ,

wherein determining the overfill factor based on the expected error in the predicted head position of the user comprises setting the overfill factor based at least in part on the first and second prediction error margins, and

wherein the overfill factor comprises a first overfill factor value for a horizontal axis and a second overfill factor value for a vertical axis, the first and second overfill factor values being different from each other.

11. The method of claim 7 ,

further comprising determining a combined FOV associated with the overfilled image based on the first predicted FOV and the second predicted FOV,

wherein determining the combined FOV based on the first predicted FOV and the second predicted FOV comprises combining (i) a first adjusted predicted FOV, wherein the first adjusted predicted FOV is determined by adding the first error margin to the first predicted FOV and (ii) a second adjusted predicted FOV, wherein the second adjusted predicted FOV is determined by adding the second error margin to the second predicted FOV.

12. The method of claim 11 , wherein the combined FOV is determined by selecting a rectangular area that comprises the first and second adjusted predicted FOVs.

13. The method of claim 11 , wherein the combined FOV is determined by selecting a hexagonal shape that comprises the first and second adjusted predicted FOVs.

14. The method of 11 , wherein rendering the overfilled image comprises applying the overfill factor with respect to a center point of the combined FOV.

15. The method of claim 5 , further comprising:

determining a time T,

wherein the time T represents a predicted scan-out time for the VR video frame comprising the overfilled image; and

predicting a field of view (FOV) of the user for the time T based on the predicted future head position of the user.

16. The method of claim 15 , further comprising:

determining an extended FOV of the user for the time T based on a direction and speed of a head rotation of the user; and

aligning a center position of the extended FOV with a center position of the predicted FOV to produce a final extended FOV, and

wherein rendering the overfilled image comprises applying the overfill factor to the final extended FOV, the overfill factor having a first overfill factor value for a horizontal axis and a second overfill factor value for a vertical axis,

wherein the first and second overfill factor values are different from each other.

17. A method performed at a server, comprising:

receiving head tracking position information from a client device, the head tracking position information associated with a user at the client device;

predicting a future head position of the user at a scan-out time for displaying a virtual reality (VR) video frame,

wherein the VR video frame is displayed to the user via the client device, and

wherein predicting the future head position of the user at the scan-out time comprises using at least in part the head tracking position information to predict the future head position of the user at the scan-out time;

determining an overfill factor based on an expected error in the predicted future head position of the user;

rendering an overfilled image based on the predicted future head position of the user and the overfill factor;

sending the VR video frame comprising the overfilled image to the client device for display to the user;

in response to a receipt of the VR video frame comprising the overfilled image at the client device, receiving timing information from the client device, the timing information comprising at least a scan-out starting time of the VR video frame comprising the rendered overfilled image; and

determining a rendering-to-scan-out latency distribution,

wherein determining the rendering-to-scan-out latency distribution comprises at least in part determining a difference between a rendering start time of the VR video frame and the scan-out starting time of the VR video frame to calculate a rendering-to-scan-out latency value of the VR video frame.

18. A system comprising,

a processor; and

a non-transitory computer-readable medium storing instructions operative, when executed by the processor, to cause the system to:

receive head tracking position information from a client device, the head tracking position information associated with a user at the client device;

predict a future head position of the user at a scan-out time for displaying a virtual reality (VR) video frame, wherein the VR video frame is displayed to the user via the client device;

determine an overfill factor based on an expected error in the predicted future head position of the user;

render an overfilled image based on the predicted future head position of the user and the overfill factor; and

send the VR video frame comprising the overfilled image to the client device for display to the user,

wherein the expected error in the predicted future head position of the user is computed based on a latency distribution, the latency distribution comprising latency metrics data for multiple VR video frames previously scanned out for display by the client device.