Accessory Camera Modules for Head-Mounted Display Tracking
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Solution Overview
Problem
Existing camera-based head-mounted displays have a limited field of view due to a fixed number of cameras, restricting the controller tracking region and inability to capture areas above and below the device.
Innovation Solution
An object tracking system with a head-mounted display and an accessory device featuring modular, pluggable accessory cameras that extend the field of view by adding additional camera modules, utilizing a second processor to assist the main processor in searching and tracking objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a fixed number of cameras are used in the head-mounted display, then the device structure remains simple and manageable, but the field of view is limited and cannot capture areas above and below the device
Solution Approach 1:
The camera system is divided into main cameras integrated in the head-mounted display and accessory cameras in separate accessory devices. This segmentation allows the field of view to be extended by adding accessory cameras without increasing the complexity of the core HMD device, as the accessory cameras can be independently configured and removed.
Solution Approach 2:
The system transitions from a fixed two-dimensional array of cameras to a three-dimensional distributed camera network by adding accessory cameras at different spatial positions. This enables coverage of areas above and below the HMD by utilizing vertical and lateral spatial dimensions.
2Area of stationary object
If accessory cameras are added to extend the field of view, then the object tracking region is expanded, but the system complexity and processing requirements increase
Solution Approach 1:
The processing system is segmented into a main processor in the HMD and accessory processors in the accessory devices. Each processor independently processes data from its associated cameras, reducing the computational burden on the main processor while expanding the overall tracking region through coordinated multi-processor operation.
3Productivity
If all camera data is processed by a single processor, then the system structure is simple, but the computing performance and tracking efficiency are limited
Solution Approach 1:
The processing workload is segmented and distributed across multiple processors - the main processor handles data from main cameras while accessory processors handle data from accessory cameras. This segmentation enables parallel processing, significantly improving tracking efficiency without requiring a single complex high-performance processor.
Solution Approach 2:
Multiple processors are merged into a coordinated system where each processor contributes to the overall object tracking function. The main processor and accessory processors work together through data exchange and coordination protocols, combining their individual capabilities to achieve superior tracking performance.
Data Source
AI summary
An object tracking method includes following steps: transmitting search information for searching for an object by a first processor during a search stage; receiving the search information and using a second processor to determine whether any of at least one accessory camera has captured an object image in the search stage. When the second processor determines that at least one of the at least one accessory camera has captured the object image, the second processor transmits notification information to the first processor and the first processor enters a tracking stage and transmits request information to the second processor. When the second processor receives the request information, the second processor performs one of the following: transmitting the object image to the first processor, wherein the first processor calculates an object pose according to the object image.