Sensor-Based Athletic Maneuver Recognition System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems fail to accurately identify and measure athletic maneuvers in extreme sports due to subjective evaluation and inability to automatically recognize and quantify fast rotations, making it challenging for virtual competitions, leaderboards, and social networks.
Innovation Solution
A computer-implemented method using intelligent sensor processing to receive video and sensor data from multiple sources, determine motion characteristics, and create a combined video displaying athletic maneuvers, enabling objective identification and characterization of athletic maneuvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional inertial sensors are used to measure fast rotations, then sensor measurements can be obtained, but the measurements are not understandable to sport participants and spectators and cannot automatically recognize athletic maneuvers
Solution Approach 1:
The patent introduces an intermediary processing system that translates raw inertial sensor measurements into comprehensible athletic maneuver identification. The system uses sensor data as an intermediary to bridge the gap between technical measurements and user understanding, automatically recognizing tricks and maneuvers while providing meaningful information to participants and spectators.
Solution Approach 2:
The patent replaces the mechanical/manual evaluation system with an automated sensor-based recognition system. Instead of relying on subjective human judgment or complex mechanical measurement devices, the system uses inertial sensors combined with automated algorithms to identify and measure athletic maneuvers, making the process both precise and understandable.
2Quantity of substance
If multiple video sources are used to capture athletic events, then a vast amount of video data is obtained, but data selection and editing becomes challenging
Solution Approach 1:
The patent uses sensor data as an intermediary to automatically select and synchronize video footage from multiple sources. The inertial sensors provide objective temporal and spatial references that mediate between the numerous video sources, enabling automated selection of relevant clips without complex manual editing processes.
Solution Approach 2:
The system implements feedback loops where sensor measurements continuously guide video selection and synchronization. The sensor data provides real-time feedback about athletic maneuvers occurring, which automatically triggers selection and processing of corresponding video segments from multiple sources, simplifying the overall data management process.
3Adaptability or versatility
If subjective evaluation is used to judge athletic maneuvers, then personal perception of difficulty and aesthetics can be captured, but accurate identification and measurement of maneuvers becomes problematic
Solution Approach 1:
The patent merges objective sensor-based maneuver identification with subjective evaluation capabilities. The system combines precise inertial measurement data with the ability to capture and analyze aesthetic and difficulty assessments, creating a hybrid evaluation system that maintains both accuracy and versatility.
Solution Approach 2:
The system achieves multi-functionality by serving both objective measurement purposes (accurate maneuver identification) and subjective evaluation purposes (aesthetic and difficulty assessment). The same sensor platform supports multiple evaluation dimensions, making the system universally applicable to different types of athletic maneuver assessment.
Data Source
AI summary
Embodiments of the present disclosure help to automatically generate video selected from multiple video sources using intelligent sensor processing, thereby providing viewers with a unique and rich viewing experience quickly and inexpensively.