| 摘要 |
A method and system for vehicular clear path detection using adaptive machine learning techniques including additional classifiers. Digital camera images are segmented into patches, from which characteristic features are extracted representing attributes such as color and texture. The patch features are analyzed by a Support Vector Machine (SVM) or other machine learning classifier, which has been previously trained to recognize clear path image regions. For image regions or patches which result in a low confidence value, an additional classifier can be used, where the additional classifier is adaptively trained using real world test samples which were previously classified with high confidence as clear path roadway. Output from the original, offline trained classifier and the additional, adaptively-updated classifier are then used to make a joint decision about clear path existence in subsequent image patches. |
