Offloading Pose Processing to Mobile Devices for Camera-Free Motion Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional entertainment devices such as TVs and set-top boxes lack cameras and sufficient processing power, making motion tracking and pose recognition challenging, and upgrading hardware is costly or impractical.
Innovation Solution
Offloading pose detection and tracking processes to mobile devices with cameras, using algorithms like deep learning networks and convolutional neural networks to transmit pose data over a network connection for enabling motion tracking on legacy entertainment hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a camera is installed on legacy entertainment devices to enable motion tracking, then motion tracking capability is achieved, but device complexity and cost increase
Solution Approach 1:
The patent introduces a mobile device as an intermediary component that performs pose estimation and tracking. Instead of integrating the camera and processing unit directly into the legacy entertainment device, the mobile device acts as a mediator that captures images, processes them to determine user pose, and transmits the data back to the entertainment device for controlling applications.
2Productivity
If processing power is upgraded on legacy entertainment devices to enable pose recognition, then motion tracking performance improves, but hardware cost increases
Solution Approach 1:
The patent extracts the computationally intensive pose estimation function from the legacy entertainment device and relocates it to the mobile device. The mobile device's processor performs the heavy computational tasks of running pose estimation algorithms on captured images, while the legacy device only handles the simpler tasks of receiving pose data and controlling applications.
3Adaptability or versatility
If a camera is added to legacy devices for motion tracking, then pose detection is enabled, but device cost increases
Solution Approach 1:
The mobile device serves as an intermediary that provides the camera functionality. Rather than requiring the legacy entertainment device to purchase and install its own camera, the user leverages their existing mobile device's camera to capture images for pose estimation, thereby avoiding the cost and complexity of adding a camera to the legacy device.
4Device complexity
If pose processing is performed on legacy devices without cameras, then device simplicity is maintained, but motion tracking functionality is lost
Solution Approach 1:
The mobile device is utilized as a universal platform that performs multiple functions: capturing images through its camera, executing pose estimation algorithms through its processor, and communicating with the legacy entertainment device through wireless connections. This multi-functional approach allows the legacy device to maintain simplicity while still achieving motion tracking functionality.
Data Source
AI summary
Systems and methods for motion tracking on a hardware device without a camera and/or without a sufficiently powerful hardware processor, by offloading pose processing fully or partially to a mobile device, are disclosed. Methods executable on the hardware device include receiving pose data associated with a user from the mobile device, and performing a touchless control of an application on the hardware device, based on the received pose data. Methods executable on the mobile device include capturing at least one image associated with a user, performing a pose recognition algorithm on the mobile device, based on the captured image, to generate pose data for performing a touchless control of an application on the hardware device, and transmitting the pose data to the hardware device, using the network connection. The methods and systems include embodiments where the pose recognition algorithm uses machine learning.