Gesture Detection Using Elliptical Representation

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Solution Overview

Problem

Existing electronic devices require a large number of photodetectors for gesture detection, which increases costs and complexity while being susceptible to noise and imperfections in optical and electrical paths, limiting their effective range and robustness.

Innovation Solution

Implementing a photodetector array with a Kalman estimator to generate a compact elliptical representation of gestures using five coefficients, reducing the number of photodetectors needed and enhancing gesture detection robustness through stochastic estimation and least squares fitting.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a large number of photodetectors are used for gesture detection, then detection coverage and reliability are improved, but device complexity and cost increase

Engineering Contradiction:

Improvegesture detection reliabilityVSAvoidphotodetector array complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent combines multiple photodetector signals into a single elliptical representation that captures the essential gesture information. Instead of processing signals from many individual photodetectors separately, the system merges them into one compact mathematical model (ellipse) defined by five coefficients, thereby reducing system complexity while maintaining detection reliability.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent creates a simplified mathematical copy (elliptical representation) of the complex photodetector array data. The ellipse coefficients serve as a compact representation that captures the gesture's essential characteristics without requiring the full complexity of the original photodetector array, enabling efficient processing with fewer components.

Inventive Principle:

Principle #26Copying

2Reliability

If more photodetectors are deployed, then gesture detection robustness improves, but susceptibility to noise and imperfections increases

Engineering Contradiction:

Improvegesture detection robustnessVSAvoidnoise susceptibility

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent extracts only the essential gesture information from the photodetector signals by fitting an ellipse to the data. This extraction process filters out noise and imperfections inherent in individual photodetector readings, keeping only the meaningful gesture characteristics represented by the five ellipse coefficients.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system uses stochastic estimation and least squares fitting to continuously refine the elliptical representation based on incoming photodetector signals. This feedback mechanism allows the system to adapt to noise and imperfections by iteratively improving the gesture representation, thereby enhancing robustness without requiring additional photodetectors.

Inventive Principle:

Principle #23Feedback

3Productivity

If a compact elliptical representation with five coefficients is used, then data processing efficiency increases, but gesture information detail may be reduced

Engineering Contradiction:

Improvegesture processing efficiencyVSAvoidgesture detail information

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent transforms the complex multivariate photodetector signal data into a simplified five-parameter elliptical representation. By changing the parameter space from many individual photodetector readings to just five ellipse coefficients (defining position, size, and orientation), the system achieves efficient processing while preserving the essential gesture information needed for recognition.

Inventive Principle:

Principle #35Parameter changes

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach increases the effective range of gesture detection, reduces false positives, and decreases equipment costs by allowing for more robust and efficient gesture recognition with fewer photodetectors, while maintaining adequate performance.

Implementation Method 1

a sensor is configured to detect a gesture and provide a signal in response thereto

Methodology Applied

Scientific EffectPhotoelectric Effect: Photoelectric Effect

Implementation Method 2

An estimator, which is in communication with the sensor, is configured to generate an elliptical representation of the gesture

Methodology Applied

Scientific EffectStochastic Estimation:

Data Source

PatentUS10055024B2Gesture detection and compact representation thereof

Publication Date: 2018.08.21 MAXIM INTEGRATED PROD INC

AI summary

Techniques are described that may be implemented with an electronic device to detect a gesture within a field of view of a sensor and generate a compact data representation of the detected gesture. In implementations, a sensor is configured to detect a gesture and provide a signal in response thereto. An estimator, which is in communication with the sensor, is configured to generate an elliptical representation of the gesture. Multiple coefficients for the compact representation of the gesture can be used to define the ellipse representing the gesture.