Pedestrian Detection Program Using HOG and LBP Feature Extraction
This program extracts HOG and LBP features from positive and negative sample images, trains a classifier using Support Vector Machines, and implements pedestrian detection. Implementation details include feature vector extraction algorithms, SVM training methodology, and sliding window detection techniques. Experimental results demonstrate effective pedestrian detection with robust performance.