Multi-User Coaching via Depth Image Stitching
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Solution Overview
Problem
Current motion-sensing systems, such as those using Kinect, are limited in their ability to provide effective multi-user coaching due to restricted detection ranges and inability to compare motion similarity across multiple users, leading to inadequate feedback on posture and motion correctness.
Innovation Solution
A multi-user coaching system that employs a depth image stitching process, multithreading processing, and a coaching database to capture and compare user motion data with virtual coach information, enabling personalized feedback and expanded motion-sensing ranges through the use of multiple motion-sensing cameras and image processing units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a single Kinect sensor is used for motion tracking, then the system can provide one-on-one coaching guidance, but the detection range is limited to 57.5° horizontal view angle
Solution Approach 1:
The patent divides the detection system into multiple Kinect sensors, each covering a specific view angle sector. The horizontal detection range is segmented into multiple 57.5° fields of view, with each sensor responsible for one sector. This segmentation allows the system to achieve a wider overall detection range while keeping each individual sensor's complexity manageable.
Solution Approach 2:
The patent merges multiple Kinect sensors into a unified detection system. By combining the output of multiple sensors through image stitching and coordinate transformation, the system achieves an expanded horizontal detection range while maintaining the functionality of individual sensors. The sensors work together as an integrated system to cover a broader area.
2Productivity
If multiple students are trained simultaneously in a gym, then the gym can serve more users, but the coach cannot provide effective individual instruction to each student
Solution Approach 1:
The system enables students to coach themselves through automated motion analysis. Each student's motion is captured by the Kinect sensor and automatically compared against reference data to generate personalized feedback. This self-service mechanism allows multiple students to receive individualized coaching attention simultaneously without requiring the human coach to be present for each student.
Solution Approach 2:
The system implements automated feedback loops that continuously monitor student motion and provide real-time guidance. The motion capture system compares each student's movements against reference data and generates immediate feedback on posture and technique correctness. This feedback mechanism enables effective individual instruction for multiple students simultaneously through automated assessment.
3Area of stationary object
If the view-angle range of the sensor is increased to cover more area, then the detection range expands, but the ability to provide personalized feedback to multiple users simultaneously deteriorates
Solution Approach 1:
The patent segments the detection space into multiple view angle sectors, with each Kinect sensor responsible for a specific sector. This segmentation allows each sensor to maintain a focused field of view for accurate motion analysis while collectively covering a wider area. The segmented approach preserves personalized feedback capability by maintaining distinct detection zones for each user.
Solution Approach 2:
The patent transitions from a single wide-angle view to a multi-dimensional detection architecture. By arranging multiple sensors in spatial dimensions and using image stitching to create a comprehensive view, the system expands detection range while maintaining the ability to analyze individual motions in detail. The multi-dimensional arrangement allows simultaneous coverage of multiple users with personalized feedback.
Data Source
AI summary
A system and a method of multi-user coaching are introduced herein. Motion-sensing cameras are applied to capture images, and a depth image stitching module is applied to perform a depth image stitching process on the captured images to expand the motion-sensing range, so as to establish a virtual environment for multi-user coaching. Each user can be coached individually by a one-to-multiple approach to improve his or her motions. By using the system and the method of multi-user coaching, that is, the system can only calculates on motion similarities of the users, and instructions are fed back to each user. Therefore, the system and the method described herein can be extensively applied to various products, such as a virtual gymnasium, a virtual aerobics classroom, a virtual Budokan, and so on.