Algorithmic optimisation of histogram intersection kernel support vector machine‐based pedestrian detection using low complexity features

Algorithmic optimisation of histogram intersection kernel support vector machine‐based pedestrian detection using low complexity features

Histogram intersection kernel support vector machine (SVM) is accepted as a better discriminator than its linear counterpart when used for pedestrian detection in images and video frames. Its computational complexity has, however, limited its use in practical real‐time detectors. To circumvent this...

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Bibliographic Details
Main Author: Muhammad Bilal
Format: Article
Language:English
Published: Wiley 2017-08-01
Series:IET Computer Vision
Subjects:
algorithmic optimisation
histogram intersection kernel support vector machine
pedestrian detection
low complexity feature detection framework
SVM
image frame
Online Access:https://doi.org/10.1049/iet-cvi.2016.0403

Internet

https://doi.org/10.1049/iet-cvi.2016.0403

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