Opposite-Surface Sensor Detection for Multi-Target Position Recognition
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Solution Overview
Problem
Conventional object detection methods using infrared light often result in erroneous recognition or loss of targets when multiple markers are close to an object, leading to unstable tracking and user experience issues in applications like air hockey.
Innovation Solution
An information processing device and method that utilize separate sensors to detect targets from opposite directions across the same surface, preventing erroneous recognition by using sensing data from top and bottom cameras to accurately track the positions of multiple detection targets on a shared surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single sensor is used to detect multiple markers on the same surface, then the device complexity is reduced, but the measurement precision deteriorates due to erroneous recognition when markers are close together
Solution Approach 1:
The detection system is segmented into multiple sensors positioned at different locations. Each sensor independently detects markers from its own perspective, allowing the system to distinguish between closely spaced markers by comparing their positions across multiple sensor viewpoints. This segmentation resolves the measurement precision issue while maintaining manageable device complexity through modular sensor arrangement.
Solution Approach 2:
The system transitions from single-plane detection to multi-plane detection by positioning sensors on opposite surfaces of the table. This dimensional change allows markers to be detected from both above and below the table surface, creating a three-dimensional detection space that eliminates ambiguity in marker identification and prevents erroneous recognition.
2Area of stationary object
If markers are placed close together on the same surface to improve spatial resolution, then the area coverage is improved, but the reliability deteriorates due to target loss and erroneous recognition
Solution Approach 1:
By dividing the detection task across multiple sensors positioned at different locations, each sensor can independently track markers within its field of view. This segmentation allows markers to be placed closer together while maintaining reliable identification, as each sensor provides independent verification of marker positions and the system can cross-reference data to prevent target loss.
Solution Approach 2:
The system implements feedback mechanisms where sensing data from multiple sensors is continuously compared and cross-validated. When markers are detected by multiple sensors, the system uses this redundant information to confirm marker identity and position, providing feedback that enhances reliability even when markers are densely positioned on the detection surface.
Data Source
AI summary
There is provided an information processing device, an information processing method, and a computer program capable of more reliably recognizing positions of a plurality of detection targets. The information processing device includes a control unit for recognizing positions of a first detection target and a second detection target that are present on the same surface. The control unit recognizes the position of the first detection target based on sensing data obtained by a first sensor for sensing the first detection target from a first direction, and recognizes the position of the second detection target based on sensing data obtained by a second sensor for sensing the second detection target from a direction opposite to the first direction across the same surface.