A pedestrian detection method using the extension of the HOG feature

Nakashima, Yuuki; Tan, Joo Kooi; Kim, Hyoungseop; Ishikawa, Seiji

doi:10.1109/scis-isis.2014.7044743

Cited by 3 publications

(1 citation statement)

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“…The pedestrian dataset resulting from their works were made available to the public where algorithms on pedestrian detection can be trained and validated. [5], [6] and [7] made optimization on the algorithm to reduce computation time and improve accuracy. In [8], an in-depth analysis of the HOG -SVM chain answering the question why HOG-SVM performs so well in people detection was made.…”

Section: Related Workmentioning

confidence: 99%

Development and Characterization of a Computer Vision System for Human Body Detection and Tracking under Low-light Condition

Llorente¹,

Dadios²

2019

IJATCSE

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Computer vision is an exciting field that integrates soft-computing algorithms and computer hardware powerful enough to handle the computation required especially if it is to be used in real-time applications. Pedestrian detection and tracking is one application of computer vision which is very useful in surveillance applications. Under this application, real-time processing of images to detect human object and perform tracking is carried out. Illumination of the scene is crucial in order the detection algorithm to carry out the computation task correctly. In this study, a computer vision system is developed for the detection and tracking of pedestrian or human body in a video. Detection and tracking of the human object is performed under different illumination. The illumination is provided using an LED lighting system where the intensity of illumination can be varied by changing the duty cycle of the pulse activating the LEDs..

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Section: Related Workmentioning

confidence: 99%