Motion Detection Sensor Mounting Position Discrimination
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Solution Overview
Problem
Current technologies face challenges in efficiently extracting scenes of interest from camera shots, particularly when a user performs specific motions, as existing motion detection technologies are not adequately developed for efficient processing.
Innovation Solution
An information processing system that includes sensors mounted on a user or objects, which detect motion and calculate ratios between high-frequency and low-frequency components in sensor data to determine if the sensor is mounted on a human body or another object, allowing for accurate motion detection and metadata generation for scene extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is used to detect user motion for scene extraction, then extraction accuracy of specific motion scenes is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent applies preliminary action by pre-defining specific motion patterns (e.g., jumping, waving) and their corresponding sensor data characteristics before actual scene extraction. The system pre-processes sensor data to identify these predefined patterns, allowing for rapid scene extraction without complex real-time analysis, thus reducing processing time while maintaining extraction accuracy.
Solution Approach 2:
The patent changes parameters by focusing on specific frequency ranges and motion intensity thresholds rather than analyzing all sensor data parameters. By transforming the problem from comprehensive motion analysis to targeted parameter detection (e.g., specific acceleration thresholds, frequency bands), the system achieves accurate scene extraction with reduced computational complexity and faster processing.
2Measurement precision
If comprehensive sensor analysis is performed to identify specific user motions, then scene extraction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies the extraction principle by isolating and analyzing only the specific sensor data elements relevant to predefined motion patterns (e.g., acceleration thresholds, frequency ranges) rather than processing comprehensive sensor data. This selective extraction of critical parameters reduces processing system complexity while maintaining scene extraction accuracy.
Solution Approach 2:
The patent segments the motion detection task into distinct, independent motion patterns (jumping, waving, running) with specific detection criteria for each. By dividing the complex analysis into separate, modular pattern recognition modules, the system reduces overall processing complexity while achieving accurate detection of specific user motions.
3Speed
If motion detection algorithms assume fixed sensor mounting positions, then processing speed is improved, but detection accuracy decreases when mounting position varies
Solution Approach 1:
The patent applies dynamics by making the motion detection algorithms adaptive to varying sensor mounting positions rather than assuming fixed positions. The system dynamically adjusts detection parameters and thresholds based on the actual mounting position detected from sensor data characteristics, maintaining high processing speed while improving motion detection accuracy across different mounting scenarios.
Data Source
AI summary
Accurate motion detection is performed by discriminating whether a sensor detecting an object motion is mounted on a human body or not, and processing is executed with respect to metadata based on the result. Sensor information according to the motion is input from the sensor, and a sensor mounting position is determined. A sensor mounting position detection unit calculates a ratio between a high-frequency component and a low-frequency component included in the sensor information, and discriminates whether the sensor is mounted on the human body or is mounted on other than the human body, on the basis of the calculated ratio. A metadata generating unit inputs user motion detection information obtained by executing a motion detection algorithm assuming a sensor mounting position coincident with a sensor mounting position detection result, and generates the shot image corresponding metadata.