3D Space Generator for Driver Intention Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current driver intention analysis systems face challenges in accurately recognizing user intentions using only motion and face expression recognition technology, which is unidirectional and requires calibration for each driver, limiting their effectiveness in analyzing driver drowsiness, distraction, and emotion.
Innovation Solution
A user intention analysis apparatus and method that utilizes a 3D space generator to create a virtual environment, a 3D image analyzer to estimate relative positions and generate contact information between body parts, an action pattern recognizer to classify user actions, and a user intention recognizer to infer intentions based on ontology, allowing for accurate and calibrated analysis of user interactions in a 3D space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion and face expression recognition technology is used, then user intention can be analyzed, but the analysis accuracy is insufficient due to unidirectional recognition limitations
Solution Approach 1:
The patent combines multiple recognition modalities (motion recognition, face expression recognition, and contact information recognition) into a unified analysis system. The intention analysis unit integrates results from these different recognition approaches to improve overall accuracy while maintaining versatility in analyzing various user states including drowsiness, distraction, and emotion.
Solution Approach 2:
The system is designed to handle multiple recognition tasks simultaneously through a single integrated platform. The same 3D space generation and image analysis infrastructure supports motion recognition, face expression recognition, and contact information extraction, making the system versatile across different user intention analysis scenarios without requiring separate specialized systems.
2Reliability
If motion recognition technology is used, then user actions can be detected, but calibration is required for each driver which increases system complexity
Solution Approach 1:
The patent uses 3D models as virtual copies of the driver's body parts (hand, head, face). These pre-established 3D models serve as reference templates that can be matched against captured image data without requiring individual calibration for each driver. The matching unit compares extracted features with these generic 3D models, eliminating the need for driver-specific calibration while maintaining reliable action detection.
Solution Approach 2:
The system transforms the calibration problem into a parameter matching problem. Instead of calibrating the system for each driver, the matching unit adjusts matching parameters (such as position, orientation, and scale) to align captured images with 3D models. This parameter-based approach allows the same system to accurately detect actions for different drivers without individual calibration procedures.
Data Source
AI summary
Provided are a user intention analysis apparatus and method based on image information of a three-dimensional (3D) space. The user intention analysis apparatus includes a 3D space generator configured to generate a 3D virtual space corresponding to an ambient environment, based on physical relative positions of a plurality of cameras and image information generated by photographing the ambient environment with the plurality of cameras, a 3D image analyzer configured to estimate a relative position between a first object and a second object included in the image information in the 3D virtual space and generate contact information of the first object and the second object, based on the relative positions of the first object and the second object, an action pattern recognizer configured to compare the contact information with a pre-learned action pattern to recognize an action pattern of a user who manipulates the first object or the second object, and a user intention recognizer configured to infer a user intention corresponding to the recognized action pattern, based on ontology.