Research on Optimized Pedestrian Detection Based on Sliding Window

Pedestrian detection is a key part of image processing technology, which needs to accurately identify the pedestrian’s images. How to improve the robustness of the detection algorithm while maintaining high detection efficiency has always been a research topic. This paper first introduces the application of pedestrian detection, then discusses the current research, and introduces the principle of Histogram of Oriented Gradient feature extraction and Support Vector Machine classifier based on a sliding window. This study helps to enhance the contrast of the test image by histogram equalization and then uses multiple training methods to improve the performance of the model. Experiments are carried out by using a self-built training set and test set, and the test results show good results.