Selective search and machine learning classification far-infrared pedestrian detection method

Abstract

The invention discloses a selective search and machine learning classification far-infrared pedestrian detection method. The method comprises the following steps: generating a candidate region from afar-infrared image by combining a selective search algorithm with a sliding window method; constructing a double-branch support vector classifier based on local intensity difference histogram featuresaccording to different heights of the candidate regions, and classifying the candidate regions to obtain a pedestrian detection box; on the basis, realizing an auxiliary driving reminding function based on pedestrian height and pedestrian motion direction estimation. The system comprises: a candidate region generation module used for acquiring pedestrian candidate regions by utilizing a selectivesearch and local sliding window technology, a candidate region classification module used for realizing candidate region classification by a double-branch support vector machine based on local intensity difference histogram features, a double-branch support vector machine training module, and a dangerous pedestrian early warning module used for estimating based on height and pedestrian movement direction. According to the method, the detection accuracy and the detection speed can be considered, the algorithm performance meets the practical requirement, and the method has an auxiliary drivingreminding function.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, image processing and computer vision assisted driving systems, and in particular relates to a far-infrared pedestrian detection method based on selective search and machine learning classification. Background technique [0002] Far-infrared, also known as thermal infrared, is imaged according to the temperature of the scene and does not depend on the lighting of the scene. It is especially suitable for vehicle-mounted assisted driving systems that need to detect pedestrians during the day and at night. However, for the pedestrian detection assisted driving system based on thermal infrared, there are currently problems in the domestic system such as low detection rate, high false alarm rate, and poor real-time performance, which make it unable to meet the actual application requirements. Therefore, the study of vehicle-mounted pedestrian detection methods based on thermal i...

AI Technical Summary

Problems solved by technology

[0008] The purpose of the embodiments of the present invention is to provide a far-infrared pedestrian detection method based on selective search and machine learning classification, aiming to solve the problem that the recognition accuracy of the existing far-infrared camera-based vehicle-mounted pedestrian detection method is not up to standard and / or insufficient. Satisfactory, real-time performance needs to be improved, and the robustness is not strong

Images