In-Cabin Gesture and Gaze Control for Low-Distraction Vehicle Interfaces
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Solution Overview
Problem
Existing vehicle infotainment and climate control systems require distracting hand movements or high-performance deep learning algorithms for gesture recognition, which can be inconvenient and inefficient, especially in varying lighting conditions.
Innovation Solution
An apparatus using an indoor camera and radar to identify hand gestures and track driver gaze, processing location and radar data to determine control commands for vehicle controls, reducing the need for high-performance hardware and improving functionality in diverse lighting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If touchscreen-based contact control is used for infotainment and air-conditioning systems, then various vehicle functions can be controlled, but driver attention is distracted and safety deteriorates
Solution Approach 1:
The patent replaces the mechanical touchscreen contact control system with a gesture recognition system using radar and camera sensors. The radar detects hand movements through electromagnetic waves while the camera captures visual gesture data, eliminating the need for physical contact with controls and thereby maintaining function control capability while removing driver distraction and safety risks
Solution Approach 2:
The patent introduces an intermediary gesture recognition system that mediates between the driver and vehicle controls. The radar and camera act as intermediaries to detect hand movements and translate them into control commands, allowing function control without direct touchscreen interaction and thus preserving safety while maintaining versatility
2Ease of operation
If deep learning algorithm is used to process images for hand movement identification, then gesture recognition can be achieved, but high-performance hardware is required and complexity increases
Solution Approach 1:
The patent merges radar detection technology with camera-based gesture recognition to create a hybrid system. The radar provides precise hand movement detection while the camera captures visual context, and their combined data is processed together to achieve accurate gesture recognition without relying solely on computationally intensive deep learning algorithms, thereby reducing hardware complexity requirements
Solution Approach 2:
The patent segments the gesture recognition task into multiple components: radar data processing for hand movement detection, camera data processing for visual gesture capture, and integrated processing for command determination. This segmentation allows each component to be optimized independently, reducing the overall computational burden and hardware complexity compared to using a single deep learning approach
3Ease of operation
If hand movement identification is performed in environments with strong sunlight or infrared lighting, then gesture control can be attempted, but identification performance degrades
Solution Approach 1:
The patent uses radar as an intermediary detection mechanism that is insensitive to lighting conditions. The radar waves penetrate through strong sunlight and infrared lighting without degradation, providing stable hand movement detection data that compensates for the camera's reduced performance in challenging lighting environments, thereby maintaining gesture control functionality and identification accuracy
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
Enables convenient and safe control of vehicle systems through gesture recognition, reducing driver distraction and operational complexity while maintaining effectiveness across different lighting conditions.
Implementation Method 1
an indoor radar configured to have a sensing area inside the vehicle and obtain radar data
Implementation Method 2
an indoor camera configured to have a field of view inside a vehicle and obtain image data
Data Source
AI summary
Disclosed herein is an apparatus for identifying a movement. The apparatus including an indoor camera having a field of view inside a vehicle and obtain image data; an indoor radar having a sensing area inside the vehicle and obtaining radar data; a controller including a first processor and a second processor, the first processor obtaining location information of a region including a driver's hand based on processing gesture image data of the driver obtained from the indoor camera; and a second processor identifying the driver's gesture by processing the location information and gesture radar data of the driver obtained from the indoor radar. The first controller determining a region of interest (ROI), to which a driver's gaze is directed, among a plurality of predetermined control target regions inside the vehicle from the image data of the driver obtained from the indoor camera and transmitting a command corresponding to the identified gesture to a control target corresponding to the ROI.