Vehicle Gesture Interface With Wrist-Aware Hand Region Recognition
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Solution Overview
Problem
Current gesture recognition systems in vehicles face challenges such as non-intuitive recognition from the driver's perspective, errors due to overlapping fingers, and unnecessary resource consumption due to constant activation, leading to misrecognition and increased computational resources.
Innovation Solution
A user interface device that varies the reference area for determining the hand area in images based on the user's hand angle, activates gesture recognition with a specific change amount, and maintains or resets the recognition state based on set values, using a processor to divide images into regions and compare hand shapes and patterns with stored user information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If gesture recognition is always activated to recognize user gestures, then gesture recognition availability is improved, but computational resource consumption increases and misrecognition occurs due to unintended user motion
Solution Approach 1:
The system activates gesture recognition periodically or on-demand rather than continuously. A camera captures images at specific intervals or when triggered, and gesture recognition is performed only during these periodic activation periods, reducing computational resource consumption while maintaining recognition availability.
Solution Approach 2:
The system performs preliminary actions such as capturing baseline images or detecting preliminary hand movement patterns before activating full gesture recognition. This preliminary detection prepares the system for upcoming gestures, allowing recognition to be activated only when necessary, thus reducing unnecessary computational resource usage.
2Reliability
If gesture recognition is always activated to recognize user gestures, then gesture recognition availability is improved, but misrecognition occurs due to unintended user motion
Solution Approach 1:
The system applies different processing quality levels to different regions or contexts. For example, it focuses computational resources on specific hand regions or gesture-critical areas in the image, rather than uniformly processing the entire image, thereby improving recognition accuracy while reducing misrecognition of unintended motions.
Solution Approach 2:
The system uses feedback mechanisms where recognition results are evaluated and used to adjust subsequent recognition parameters. If misrecognition is detected, the system can adjust sensitivity thresholds or activation criteria based on feedback from previous recognition attempts, improving overall accuracy and reducing false positives.
3Adaptability or versatility
If the number of fingers is recognized by obtaining an image of the user's hand to determine gestures, then gesture recognition capability is provided, but recognition errors occur due to overlapping fingers and non-intuitive recognition from driver's steering control perspective
Solution Approach 1:
The system dynamically adjusts recognition parameters such as reference area size and shape based on the detected hand angle and gesture context. Instead of using a fixed reference area, the system adapts the reference area dynamically to match the hand's orientation and the specific gesture being performed, improving recognition accuracy for various finger configurations.
Solution Approach 2:
The system changes recognition parameters such as the reference area for determining hand occupancy based on the hand angle. By adjusting parameters like reference area size, shape, or position according to the detected hand orientation, the system improves recognition accuracy for different gestures while reducing errors from overlapping fingers.
Data Source
AI summary
A user interface device which receives a user instruction for controlling at least one electronic device, includes a camera configured to obtain an image of a user; and at least one processor configured to divide the obtained image into a plurality of regions, determine an area occupied by the user's hand in each of the divided regions, and recognize gesture of the user based on the area occupied by the user's hand, wherein the at least one processor may be further configured to determine a direction in which the user's wrist faces based on the obtained image, and divide the obtained image into the plurality of regions based on the direction of the user's wrist.