Driver lane changing intention recognition method based on Gaussian mixture hidden Markov model
A Gaussian mixture, driving intent technology, applied in character and pattern recognition, computational models, machine learning, etc., can solve the driver's nervous attention, distraction and other problems
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment Construction
[0104] A driver's lane-changing intention recognition method based on a Gaussian mixture hidden Markov model includes the following steps:
[0105] Step 1, determine the frame where the face area is located and the coordinates corresponding to the horizontal direction of the left and right borders of the frame, and extract the driver's face area based on the YCbCr color space for skin color extraction, to obtain a rough positioning map of the face;
[0106] Step 2. Human eye positioning based on the ASEF (Average of Synthetic Exact Filters) filter. First, the filter needs to be trained using pictures, and the driver video data obtained through the driving recorder is disassembled into a sequence of pictures as training samples. Manually specify the center position of the left eye and right eye for each picture as the output, so that each sequence picture and output are a pair of training pairs, and the training pair is input into the ASEF filter for training, and the human eye ...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com