%0 Journal Article
%T Pedestrian Detection with Improved LBP and Hog Algorithm
%A Wei Zhou
%A Suyun Luo
%J Open Access Library Journal
%V 5
%N 4
%P 1-10
%@ 2333-9721
%D 2018
%I Open Access Library
%R 10.4236/oalib.1104573
%X <div style="text-align:justify;">
	<span style="line-height:1.5;">This article aims to improve the HOG   SVM
pedestrian detection method proposed by previous researchers. The speed of HOG   SVM to
detect pedestrians is relatively slow, and the detection accuracy is not very
good. This paper proposes a PCA (principal component analysis) dimension reduction
for HOG and also interpolates it. The article combines the dimensions of
individual HOG features and improves th</span><span style="line-height:1.5;">eir accuracy, and fuses them with
improved LBP features. The features of the fusion of HOG features and LBP
features can both express pedestrian profile information and obtain pedestrian
texture information. This can improve the speed of pedestrian detection and
improve the accuracy of detection, which is beneficial to reduce false
detection and missed detection. Although some researchers have combined the two
features of HOG and LBP, after simple fusion of these two features, the
experimental results show that the detection effect is not much improved. This
article is aimed at different formats of video detection material, an
application program written on the MFC platform, making pedestrian detection of
the material quickly verified, which is conducive to pedestrian detection
results data analysis and recording.</span>
</div>
%K HOG Feature
%K Improved LBP Feature
%K MFC
%U http://www.oalib.com/paper/5293659