RF Sensing Control for Camera FOV and Partial Frame Capture
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Solution Overview
Problem
Wireless electronic devices face challenges in efficiently managing power consumption and network resources, particularly in extended reality applications, due to the need for continuous tracking and capturing of objects that may be outside the camera's field-of-view or obstructed, leading to increased power consumption and network traffic.
Innovation Solution
Utilizing radio frequency (RF) sensing to detect the location and movement of objects relative to the device, allowing for the control of camera settings and generation of partial images or frames based on RF sensing data, reducing unnecessary power consumption and network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the image capturing device continuously captures objects outside the field-of-view or obstructed objects, then the tracking accuracy and reliability are improved, but the power consumption increases
Solution Approach 1:
The system performs preliminary RF sensing to detect objects before they enter the camera's field-of-view. By anticipating object movement and pre-positioning the camera, the system avoids unnecessary continuous capturing while ensuring reliable tracking when objects become visible.
Solution Approach 2:
RF sensing acts as an intermediary between the camera and the environment. It provides spatial awareness of objects outside the camera's FOV, enabling intelligent control of camera operation to balance tracking reliability with power consumption.
2Measurement precision
If the image capturing device continuously captures and transmits data, then the object detection accuracy is improved, but the network traffic increases
Solution Approach 1:
Instead of continuously capturing and transmitting all image data, the system performs partial capturing based on RF sensing results. Only necessary image data is captured and transmitted when objects are detected to be within or approaching the field-of-view, reducing network traffic while maintaining detection accuracy.
Solution Approach 2:
RF sensing performs preliminary detection of objects and their trajectories before triggering camera capture. This preliminary action filters out unnecessary data transmission, ensuring only relevant object information is sent over the network.
3Adaptability or versatility
If the camera captures all objects in the environment, then the completeness of object tracking is improved, but the device complexity increases
Solution Approach 1:
The system segments the tracking task into two parts: RF sensing handles the detection and spatial mapping of objects in the entire environment, while the camera focuses only on capturing objects that are or will be within its field-of-view. This segmentation reduces the complexity burden on the camera system while maintaining comprehensive object tracking.
Solution Approach 2:
RF sensing serves as an intermediary system that complements the camera. It provides environmental context and object location information, enabling the camera to focus on specific targets rather than capturing everything, thus reducing overall system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces power consumption and network traffic by optimizing camera usage and generating partial frames, enhancing battery life and network efficiency in extended reality applications.
Implementation Method 1
determine, based on the RF sensing data, one or more reflected paths of one or more reflected RF signals, wherein each reflected RF signal comprises a reflection of a transmitted RF signal from one or more objects in a physical space
Data Source
AI summary
Disclosed are systems and techniques for extended reality optimizations using radio frequency (RF) sensing. An example method can include obtaining RF sensing data; determining, based on the RF sensing data, reflected paths of one or more reflected RF signals, each reflected RF signal including a reflection of a transmitted signal from one or more objects in physical space; comparing the one or more reflected paths, to a field-of-view (FOV) of an image sensor of the device; and based on the comparison, triggering an action by the device and/or the image sensor.