Adaptive simultaneous localization and mapping (SLAM) using world-facing cameras in virtual, augmented, and mixed reality (xR) applications
Systems and methods for adaptive Simultaneous Localization and Mapping (SLAM) using world-facing cameras in virtual, augmented, and mixed reality (xR) applications. An Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: select at least one region-of-interest (ROI) within an image captured by a camera mounted on a Head-Mounted Display (HMD) worn by a user in a physical environment during execution of a virtual, augmented, or mixed reality (xR) application; and manage utilization of an IHS resource, at least in part, by creating a map of the physical environment and tracking a location of the HMD using the at least one ROI to the exclusion of another portion of the image.
1. An Information Handling System (IHS), comprising:
a processor; and
a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to:
select one or more regions-of-interest (ROIs) within an image captured by a camera mounted on a Head-Mounted Display (HMD) worn by a user in a physical environment during execution of a virtual, augmented, or mixed reality (xR) application;
monitor utilization of an IHS resource while the IHS performs a Simultaneous Localization and Mapping (SLAM) process on the one or more ROIs; and
modify a number of the one or more ROIs while the IHS performs the SLAM process to store a calibration curve or table that associates different numbers of ROIs with a level of utilization of the IHS resource;
select at least one ROI within the image; and
manage utilization of the IHS resource, at least in part, by creating a map of the physical environment and tracking a location of the HMD using the at least one ROI to the exclusion of another portion of the image.
2. The IHS of claim 1 , wherein the at least one ROI is selected to maintain the utilization of the IHS resource below a predetermined value.
3. The IHS of claim 2 , wherein the calibration curve or table associates a reduction in a number of ROIs with a corresponding reduction in utilization of the IHS resource.
4. The IHS of claim 3 , wherein the program instructions, upon execution, further cause the IHS to:
identify an increase in utilization of the IHS resource; and
reduce the number of the at least one ROI to avoid reaching a maximum utilization level.
5. The IHS of claim 2 , wherein the calibration curve or table associates an increase in a number of ROIs with a corresponding increase in utilization of the IHS resource.
6. The IHS of claim 5 , wherein the program instructions, upon execution, further cause the IHS to:
identify a decrease in utilization of the IHS resource; and
increase the number of the at least one ROI without reaching a maximum utilization level.
7. The IHS of claim 1 , wherein the at least one ROI comprises a plurality of pixels selected to maintain the utilization of the IHS resource below a predetermined amount.
8. The IHS of claim 7 , wherein the calibration curve or table associates a reduction in the number of pixels with a corresponding reduction in utilization of the IHS resource.
9. The IHS of claim 8 , wherein the program instructions, upon execution, further cause the IHS to:
identify an increase in utilization of the IHS resource; and
reduce the number of pixels of the at least one ROI to avoid reaching a maximum utilization level.
10. The IHS of claim 7 , wherein the calibration curve or table associates an increase in the number of pixels with a corresponding increase in utilization of the IHS resource.
11. The IHS of claim 10 , wherein the program instructions, upon execution, further cause the IHS to:
identify a decrease in utilization of the IHS resource; and
increase the number of pixels of the at least one ROI without reaching a maximum utilization level.
12. A method, comprising:
selecting one or more regions-of-interest (ROIs) within an image captured by a camera mounted on a Head-Mounted Display (HMD) worn by a user in a physical environment during execution of a virtual, augmented, or mixed reality (xR) application;
monitoring utilization of a resource while an Information Handling System (IHS) performs a Simultaneous Localization and Mapping (SLAM) process on the one or more ROIs;
modifying a number of the one or more ROIs used while the IHS performs the SLAM process to store a calibration curve or table that associates different numbers of ROIs with a level of utilization of the resource;
selecting at least one ROI within the image; and
managing utilization of the resource, at least in part, by creating a map of the physical environment and tracking a location of the HMD using the at least one ROI to the exclusion of another portion of the image.
13. The method of claim 12 , further comprising using a selected number of ROIs that results in a selected level of utilization of the resource based upon the calibration curve or table.
14. The method of claim 13 , further comprising:
identifying an increase in the level of utilization of the resource; and
reducing the number of one or more ROIs used to avoid reaching a maximum level.
15. The method of claim 14 , further comprising:
identifying a decrease in the level of utilization of the resource; and
increasing the number of one or more ROIs used without reaching the maximum level.
16. The method of claim 12 , further comprising modifying a number of pixels within each of the one or more ROIs, and storing another calibration curve or table that associates different sizes of each ROI with a level of utilization of the resource.
17. The method of claim 16 , further comprising using a selected number of pixels for each of the one or more ROIs that results in a selected level of utilization of the resource based upon the calibration curve or table.
18. The method of claim 17 , further comprising:
identifying an increase in the level of utilization of the resource; and
reducing the size of each of the one or more ROIs to avoid reaching a maximum resource utilization level.
19. The method of claim 18 , further comprising:
identifying a decrease in the level of utilization of the resource; and
increasing the size of each of the one or more ROIs without reaching the maximum resource utilization level.
20. A hardware memory device having program instructions stored thereon that, upon execution by a processor of an Information Handling System (IHS), cause the IHS to:
select one or more regions-of-interest (ROIs) within an image captured by a camera mounted on a Head-Mounted Display (HMD) worn by a user in a physical environment during execution of a virtual, augmented, or mixed reality (xR) application;
monitor utilization of an IHS resource while the IHS performs a Simultaneous Localization and Mapping (SLAM) process on the one or more ROIs; and
modify a number of the one or more ROIs while the IHS performs the SLAM process to store a calibration curve or table that associates different numbers of ROIs with a level of utilization of the IHS resource;
select at least one ROI within the image; and
manage utilization of the IHS resource, at least in part, by creating a map of the physical environment and tracking a location of the HMD using the at least one ROI to the exclusion of another portion of the image.