A Symmetry Search and Filtering Algorithm for Vision Based Pedestrian Detection System

Abstract

In this paper we present a fast symmetry search and filtering algorithm for monocular vision based pedestrian candidate detection application. First the ROI of symmetry search is focused on the pedestrian leg region, where the background is relatively simple ground plane. Afterward, the search region is divided into 2 x 4 sub blocks and symmetry density and distribution of each sub block is calculated. Finally, by comparing the symmetry density and distribution of the sub blocks, the correct symmetry axis of the pedestrian candidate is search and also some no-pedestrian candidates are filtered out. The results shown in this method are fast, cost effective and well suited for real-time vision applications.

A Boosted 3-D PCA Algorithm Based on Efficient Analysis Method

“…Accordingly, CNN-based image detection cannot be easy to trust the judgment of autonomous vehicles controlled because it cannot be confirmed to trust a basis to calculate an estimated value for the detection result. The main cause for this problem is that the CNN structure consists of complex functions with many non-linear elements to calculate the detection result [5][6][7][8][9][10][11][12][13][14]. Therefore, a detection system that can reliably determine the judgment of an autonomous vehicle by analyzing the characteristics of an object along with high-precision result inference may be required.…”

Method of Human Detection using Edge Symmetry and Feature Vector

“…먼저, 사람을 검출하기 위해 사용되는 카메라 수에 따른 영상 획득 방법은 한 대 카메라를 사용하는 방법 [2][3][4][5][6][7][8][9][10][11][12] [14,24], 신경망(Neural Netw orks) [15], 에이타부스트(Adaboost) [18][19][20][21] 이것을 간단하게 마스크를 이용하여 나타내면 그림 4와 같다. …”