Gesture Recognition on Curved Screens Using Non-Cartesian Coordinates
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Solution Overview
Problem
Existing gesture recognition systems face challenges in accurately processing gestures on curved screens, particularly in handling overlapping coordinate systems and ensuring precise control of graphic objects, which is essential for advanced human-machine interfaces in increasingly complex technical devices.
Innovation Solution
A method and device for gesture recognition that utilize a gesture recognition unit with sensors to detect the position and distance of objects, employing a non-Cartesian gesture recognition coordinate system and multiple sensors to achieve precise positioning, and prioritize gesture recognition based on image object hierarchy, allowing for efficient control of graphic objects on curved screens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple sensor coordinate systems are used to cover the detection range, then the coverage area is improved, but the complexity of processing overlapping coordinate systems increases
Solution Approach 1:
The detection space is divided into multiple sensor coordinate systems, each responsible for a specific region. This segmentation allows comprehensive coverage while enabling independent processing of each coordinate system, reducing the overall processing complexity through modular architecture.
Solution Approach 2:
A gesture coordinate system is introduced as an intermediary between multiple sensor coordinate systems and the final gesture recognition. This intermediate coordinate system serves as a common reference frame that simplifies the integration and processing of data from multiple sensors, reducing the complexity of directly handling overlapping coordinate systems.
2Measurement precision
If a non-Cartesian gesture recognition coordinate system is used, then the precision of gesture control is improved, but the complexity of the recognition system increases
Solution Approach 1:
The coordinate system is transformed from Cartesian to a non-Cartesian system that better suits gesture recognition requirements. This parameter change in the mathematical representation enables more precise mapping of gesture movements while the underlying processing architecture remains systematic and manageable.
Solution Approach 2:
The gesture coordinate system acts as an intermediary layer that translates complex sensor data into a format suitable for gesture recognition. This intermediate representation simplifies the relationship between physical sensor measurements and logical gesture interpretations, making the system more precise without proportionally increasing complexity.
3Productivity
If priority or hierarchy is assigned to image objects, then the efficiency of gesture recognition is improved, but the complexity of object management increases
Solution Approach 1:
Priorities and hierarchies for image objects are predetermined and established before gesture recognition occurs. This preliminary organization of objects into hierarchical structures enables efficient gesture recognition by pre-establishing processing priorities, reducing the computational burden during actual gesture interaction while maintaining systematic object management.
Data Source
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AI summary
Device and method for gesture recognition by means of a gesture recognition device with a screen (3) for displaying graphic data or an image object (120, 121, 122) and with a gesture recognition unit (5) comprising a sensor (100, 101, 102, 103) for detecting an object and the distance of the object.The procedure comprises the following steps: detecting the position of an object or a change in the object's position, determining the distance of the object from the screen (3) using a sensor (100, 101, 102, 103), determining the position of the object or the change in position using a position detection algorithm, whereby the position is determined in a sensor coordinate system (115, 116, 117, 118) within the detection range of the sensor (100, 101, 102, 103), determining the position of the object in a gesture recognition coordinate system (130, 131, 132), which is a three-dimensional non-Cartesian coordinate system, and recognizing a gesture from the determined position or change in the object's position.