AR Body Guidance via Depth and Visual Stream Pose Estimation
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Solution Overview
Problem
Current techniques for positioning and guiding the body, such as physical therapy or exercise, often require professional assistance or dedicated hardware, which may be unavailable, expensive, or inconvenient, and are limited in their ability to provide accurate and objective feedback.
Innovation Solution
An augmented reality body guidance system using cameras to generate depth and visual video streams, processed by a computing device with trained learning machines to identify and estimate body joint positions, overlaying pose estimates and target poses in real-time on a video display, and providing feedback on deviations for users to achieve correct positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional assistance (therapists, trainers, coaches) is used to guide body positioning, then positioning accuracy is improved, but cost and availability deteriorate
Solution Approach 1:
The system creates a virtual copy of professional guidance by using computer vision algorithms to detect and analyze body pose, replicating the expertise of therapists and trainers through automated image processing and pose estimation algorithms
Solution Approach 2:
The patent replaces the mechanical system of human professionals with an automated computer vision system that uses cameras, depth sensors, and machine learning models to perform pose detection and guidance, eliminating the need for physical presence of experts
2Measurement precision
If dedicated hardware is used to capture movement, then measurement precision is improved, but device complexity and cost deteriorate
Solution Approach 1:
The system makes the camera device universal by enabling it to perform multiple functions: capturing visual video streams, generating depth maps, detecting body pose, and providing guidance feedback, all through software processing of standard camera inputs
Solution Approach 2:
The patent creates a virtual depth map copy from standard camera images using machine learning algorithms, eliminating the need for specialized depth-sensing hardware while achieving accurate 3D pose estimation
3Ease of operation
If real-time feedback is provided through augmented reality overlay, then ease of operation is improved, but processing speed requirements deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-processing video frames to generate depth maps and detect body keypoints before overlaying the augmented reality feedback, preparing all necessary data in advance to minimize real-time processing delays
Solution Approach 2:
The patent maintains continuous processing of video streams with constant pose detection and feedback generation, ensuring uninterrupted real-time guidance while optimizing computational efficiency through continuous frame analysis
Data Source
AI summary
The disclosure relates to a system for providing guidance for positioning a body. The system may include a video display, one or more digital cameras configured to generate a depth video stream and a visual video stream, and a computing device including, a memory, and a processor. The processor may control the one or more digital cameras to generate the depth video stream including a depth image of the body and the visual video stream including a color image of the body. The processor identifies at least a part of the body within the images using a first trained learning machine to segment the images and isolate the body. The processor may crop both the visual image and the depth image based on the identified body. The processor may estimate a position of a plurality of joints of the body by applying a second trained learning machine to the identified and isolated part of the body. The processor may generate a current pose estimate by connecting estimated positions of the plurality of joints. The processor may overlay a visual representation of the current pose estimate over the color video stream on the video display.