Optimizing head mounted displays for augmented reality
While many augmented reality systems provide “see-through” transparent or translucent displays upon which to project virtual objects, many virtual reality systems instead employ opaque, enclosed screens. Indeed, eliminating the user's perception of the real-world may be integral to some successful virtual reality experiences. Thus, head mounted displays designed exclusively for virtual reality experiences may not be easily repurposed to capture significant portions of the augmented reality market. Various of the disclosed embodiments facilitate the repurposing of a virtual reality device for augmented reality use. Particularly, by anticipating user head motion, embodiments may facilitate scene renderings better aligned with user expectations than naïve renderings generated within the enclosed field of view. In some embodiments, the system may use procedural mapping methods to generate a virtual model of the environment. The system may then use this model to supplement the anticipatory rendering.
1. A system comprising:
memory including instructions;
at least one processor to execute the instructions to, at least:
retrieve an initial image during a first time;
impose a border constraint on a first portion of the initial image, the border constraint outside a field of view, the border constraint to cause a second portion of the initial image to be within the field of view during the first time; and cause a subset of the first portion of the initial image to be within the field of view during a second time in response to receiving inertial measurement unit (IMU) data.
2. The system as defined in claim 1 , wherein the at least one processor is to retrieve the IMU data at a rate faster than a camera capture rate corresponding to a second image.
3. The system as defined in claim 2 , wherein the at least one processor is to determine a predicted pose during the second time, the predicted pose indicative of user head movement.
4. The system as defined in claim 2 , wherein the at least one processor is to apply at least one of positional or rotational velocity data to determine a predicted pose during the second time.
5. The system as defined in claim 4 , wherein the at least one processor is to apply a Kalman filter to determine the predicted pose.
6. The system as defined in claim 1 , wherein the at least one processor is to reduce user nausea by rendering the subset of the first portion of the initial image from the border constraint to the field of view of a movable display.
7. The system as defined in claim 1 , wherein the at least one processor is to render a second image during a third time as a mesh in response to detecting the IMU data during the second time.
8. A computer implemented method, comprising:
retrieving, by executing an instruction with at least one processor, an image during a first time;
imposing, by executing an instruction with the at least one processor, a border constraint on a first portion of the image, the border constraint outside a field of view, the border constraint to cause a second portion of the image to be within the field of view during the first time;
causing, by executing an instruction with the at least one processor, a subset of the first portion of the image to be within the field of view during a second time in response to receiving inertial measurement unit (IMU) data; and
reducing user nausea, by executing an instruction with the at least one processor, by rendering the subset of the first portion of the image from the border constraint to the field of view of a moveable display.
9. The method as defined in claim 8 , further including retrieving the IMU data at a rate faster than a camera capture rate corresponding to a second image.
10. The method as defined in claim 9 , further including determining a predicted pose during the second time, the predicted pose indicative of user head movement.
11. The method as defined in claim 9 , further including applying at least one of positional velocity data or rotational velocity data to determine a predicted pose during the second time.
12. The method as defined in claim 11 , further including applying a Kalman filter to determine the predicted pose.
13. The method as defined in claim 8 , further including rendering a second image during a third time as a mesh in response to detecting the IMU data during the second time.