The invention discloses a monocular far-infrared pedestrian detection method based on feature fusion, and the method comprises the following steps of zooming an original infrared image according to different proportions, and obtaining a corresponding zoomed infrared image; carrying out local adaptive double-threshold segmentation binaryzation on the scaled infrared image; carrying out morphological processing on the obtained binary image; searching the processed binary image, and filtering the binary image to obtain a preliminary candidate region (ROIs); carrying out window sliding on the preliminary ROIs to obtain a series of sliding window ROIs; calculating the feature values of the ROIs, carrying out the normalization processing, and then inputting the feature values into a first SVM classifier and a second SVM classifier to be cascaded for decision making, and obtaining a preliminary pedestrian detection box; calling a non-maximum suppression algorithm to calculate the preliminarypedestrian detection box to obtain a final pedestrian detection box. The method can adapt to different distance detection, overcomes the pedestrian image breakage condition, and enables the pedestriandetection accuracy to be improved.