3D Gesture Control for Multi-Device Spatial Targeting
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Solution Overview
Problem
Existing intelligent equipment systems require unique gestures for each device, leading to a low gesture reuse rate as one gesture can only control one operation of single intelligent equipment, making it impossible to control different equipment with a single gesture.
Innovation Solution
A control method that determines the positional relationship between a control gesture and multiple intelligent equipment using depth images and positional information, allowing the same gesture to control multiple devices by identifying a target based on preset conditions, such as included angles, to improve gesture reuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If each intelligent equipment has a unique set of gestures, then the intended device can be controlled without accidentally controlling a different device, but the gesture reuse rate becomes low
Solution Approach 1:
The patent introduces a central control device as an intermediary that receives gestures from users and determines which intelligent equipment should be controlled based on spatial relationships. The depth image acquisition device captures the user's gesture and its position in 3D space, and the central control device uses this spatial information to identify the target equipment. This mediator approach allows a single gesture to potentially control multiple different equipment depending on its position, thereby increasing gesture reuse rate while maintaining control accuracy through spatial discrimination.
Solution Approach 2:
The patent transitions from 2D gesture recognition to 3D spatial gesture recognition by using depth images. Instead of relying solely on gesture type for device identification, the system incorporates the third dimension (spatial position and distance) to determine the target equipment. The depth information provides additional degrees of freedom, allowing the same gesture performed at different positions or orientations to control different equipment, thus improving gesture versatility without sacrificing control precision.
2Device complexity
If one gesture controls only one operation of single intelligent equipment, then the control system remains simple, but the gesture reuse rate becomes low
Solution Approach 1:
The system enables self-service control where the intelligent equipment automatically determines the target device based on the spatial relationship between the user's gesture and the equipment positions. The depth image processing and equipment identification are performed automatically without requiring complex user input or manual device selection. This self-determining mechanism allows one gesture to control multiple operations across different equipment while keeping the control interface simple and intuitive.
3Adaptability or versatility
If depth image processing is used to determine positional relationships, then multiple equipment can be controlled with one gesture, but the processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing the spatial positions of all intelligent equipment in the environment before gesture recognition begins. The depth camera and central control device have already mapped the 3D positions of equipment, so when a gesture is made, the system only needs to compare the gesture's spatial coordinates against the pre-stored equipment positions. This preliminary spatial mapping reduces the real-time processing complexity while enabling multi-equipment control through depth image analysis.
Data Source
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AI summary
A control method for intelligent equipment includes: determining a positional relationship between a control gesture and various intelligent equipment according to a depth image containing the control gesture and positional information of various intelligent equipment, wherein the control gesture is a gesture made by a user to control various intelligent equipment; and starting an equipment control operation on a target intelligent equipment based on the control gesture in response to determining that a positional relationship between the target intelligent equipment and the control gesture meets a preset condition.