Gesture Recognition System False Detection Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing gesture recognition technologies struggle to reliably distinguish between real and false gestures, particularly when gestures are performed close to or far from cameras, or when multiple users are present, leading to accidental or fraudulent gesture recognition.
Innovation Solution
A method and system for identifying gestures associated with a target object, which involves obtaining an image, identifying a region of interest (ROI), obtaining feature vectors and traversal path estimates, and determining whether the gesture is real or false based on these features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If gesture recognition technology is used to control devices, then hands-free interaction and user experience are enhanced, but the system cannot reliably distinguish between real gestures and false gestures
Solution Approach 1:
The patent segments gesture recognition into multiple independent verification components: hand shape analysis, movement trajectory validation, speed verification, and acceleration checking. Each component evaluates a specific aspect of the gesture and combines results to determine authenticity, preventing false gestures from triggering actions
Solution Approach 2:
The system dynamically adjusts recognition parameters such as speed thresholds, acceleration limits, and trajectory deviation tolerances based on the specific gesture type and context. This allows the system to maintain high reliability across different gesture scenarios while preserving ease of operation
2Measurement precision
If high resolution cameras are used to track hand movements, then gesture detection capability is improved, but false detection increases when hand is too close or too far from cameras
Solution Approach 1:
The patent implements dynamic field-of-view adjustment and focal point shifting based on detected hand position. When the hand moves too close or too far, the system automatically adjusts camera parameters and selection criteria to maintain optimal tracking, ensuring reliable detection across varying distances
Solution Approach 2:
The system introduces intermediate validation layers including trajectory prediction models and contextual verification that act as mediators between raw camera data and gesture recognition decisions. These intermediaries filter out false detections caused by distance-related tracking errors
3Adaptability or versatility
If gesture recognition is implemented in public spaces, then touchless technology adoption is improved, but gestures from other users may be mistakenly recognized
Solution Approach 1:
The patent employs asymmetric gesture validation where the system learns and stores each user's unique gesture patterns, speeds, and trajectories. When a gesture is detected, it is compared against the specific user's profile rather than generic patterns, making it difficult for other users to accidentally or deliberately trigger actions
Solution Approach 2:
The system performs preliminary user identification and gesture profile loading before gesture recognition begins. This preliminary action ensures that the correct user-specific parameters and thresholds are active, preventing cross-user gesture misrecognition in public spaces
Data Source
AI summary
A method for identifying a gesture associated with a target object may include receiving an image associated with the target object; identifying a region of interest (ROI) within the image associated with the target object; determining one or more feature vectors associated with the target object based on the ROI; generating a traversal path estimate based on the image and the ROI, the traversal path estimate being indicative of a region of movement of the target object; determining, based on the one or more feature vectors and the traversal path estimate, whether the gesture associated with the target object is one of a false gesture or a real gesture; and triggering a response based on the gesture being determined to be a false gesture or a real gesture.