Pedestrian detection method and device based on characteristic combination

Abstract

The invention discloses a pedestrian detection method and a device based on a characteristic combination. The method comprises that: training is performed on positive and negative samples of pedestrians, Hog characteristics and LBP characteristics of the samples are extracted and combined to form characteristic vectors of the samples; then a cascaded rejection mechanism and the characteristic vectors of the samples are combined via a cascaded linear SVM classifier which performs classification from simple ones to complicated ones so that a cascaded linear SVM pedestrian classifier is realized. The device comprises: (1) an image acquisition module: images in front of a vehicle are acquired by utilizing a vehicle-mounted pick-up head; (2) an image detection and processing module: de-noising and enhancement processing is performed on the acquired images, and pedestrian detection is performed by utilizing the loaded and trained classifier; and (3) an image display module: the pedestrians in the acquired images are identified by using rectangle frames and prompted on a vehicle-mounted DVD display screen. Technical problems of reducing false detection rate and enhancing accuracy are mainly solved by the pedestrian detection method and the device based on the characteristic combination.

Description

technical field [0001] The invention relates to the technical fields of safe driving of vehicles and image processing, in particular to a pedestrian detection method and device based on feature combination. Background technique [0002] In the fields of intelligent monitoring, intelligent transportation and robotics, the detection of pedestrians has high application value. Nowadays, computers are developing very rapidly, and the performance of computers is getting stronger and stronger, while the price is getting lower and lower. People hope that through the intervention of computer, it can help realize the rapid detection of pedestrians in the image. Therefore, pedestrian detection has become a research hotspot. [0003] Typical pedestrian detection methods include contour-based image matching and feature-based statistical methods. In the case of motion, pedestrian detection not only has difficulties such as clothing changes and posture changes, but is also affected by r...

AI Technical Summary

Problems solved by technology

The existing pedestrian detection technology generally adopts the Adaboost classification method based on Haar features. Although the efficiency of pedestrian detection is relatively good, there are many false detections. Therefore, it is necessary to improve the accuracy of detection.

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