Zenithal Pedestrian Detection Using Multiple Feature Fusion in Monocular Vision

Authors

Chunhui Tang, 1. Engineering Research Center of Optical Instrument and System of Ministry of Education, School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;;2. Shanghai Key Laboratory of Modern Optical System,School of Optical Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;

Abstract

Abstract: There were extensive literatures on pedestrian detection, mostly supposed that visible humans were observed in flat view. Sometimes pedestrian detection from another perspective should be considered. The pedestrian detection with a vertical view camera was taken into account, which was usually used to count the pedestrian number. A method is put forward for zenithal pedestrian detecting based on rectangular partition features, in which the pedestrian head detection takes place of the body detection. It is by the exhaustive scanning to find targets in an image and so all the candidates are put into a series of rectangular feature in cascade and most candidates without objects can quickly be filtered out. Then the final targets can be got by calculating the intensity variance of rectangular block to detect target color uniformity, and using the Hough Transform to detect arc contour of targets. Experiments verify it effective.

Recommended Citation

Tang, Chunhui (2020) "Zenithal Pedestrian Detection Using Multiple Feature Fusion in Monocular Vision," Journal of System Simulation: Vol. 28: Iss. 9, Article 33.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss9/33

First Page

2146

Revised Date

2015-08-24

DOI Link

https://doi.org/

Last Page

2153

CLC

TP391.4

Recommended Citation

Tang Chunhui. Zenithal Pedestrian Detection Using Multiple Feature Fusion in Monocular Vision[J]. Journal of System Simulation, 2016, 28(9): 2146-2153.