A Novel Human Detection Algorithm Based on Foreground Segmentation
DOI:
10.3993/jfbi09201306
Journal of Fiber Bioengineering & Informatics, 6 (2013), pp. 285-292.
Published online: 2013-06
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@Article{JFBI-6-285,
author = {Chunguang Liu, Zhiheng Gong, Huijie Zhu, Yanan Liu, Yue Zhou and Zhonghua Han },
title = {A Novel Human Detection Algorithm Based on Foreground Segmentation},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2013},
volume = {6},
number = {3},
pages = {285--292},
abstract = {In computer vision applications, human detection occupies an important position. HOG (Histograms
of Oriented Gradient) is a classical algorithm which was used in the area of object detection. But the
complex background would greatly affect the test accuracy when taking HOG as a human characteristic
for human detection. In order to improve the accuracy of human detection, this paper applied a new
algorithm which was based on foreground segmentation. We could get each closed region by Oriented
Watershed Transform and Ultrametric Contour Map, then the foreground and the background could be
distinguished. Finally we removed the background and calculated the foreground characteristic. The
experimental results show that this approach was effective in improving detection accuracy.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbi09201306},
url = {http://global-sci.org/intro/article_detail/jfbi/4842.html}
}
TY - JOUR
T1 - A Novel Human Detection Algorithm Based on Foreground Segmentation
AU - Chunguang Liu, Zhiheng Gong, Huijie Zhu, Yanan Liu, Yue Zhou & Zhonghua Han
JO - Journal of Fiber Bioengineering and Informatics
VL - 3
SP - 285
EP - 292
PY - 2013
DA - 2013/06
SN - 6
DO - http://doi.org/10.3993/jfbi09201306
UR - https://global-sci.org/intro/article_detail/jfbi/4842.html
KW - Human Detection
KW - HOG
KW - Foreground Segmentation
KW - Closed Region
AB - In computer vision applications, human detection occupies an important position. HOG (Histograms
of Oriented Gradient) is a classical algorithm which was used in the area of object detection. But the
complex background would greatly affect the test accuracy when taking HOG as a human characteristic
for human detection. In order to improve the accuracy of human detection, this paper applied a new
algorithm which was based on foreground segmentation. We could get each closed region by Oriented
Watershed Transform and Ultrametric Contour Map, then the foreground and the background could be
distinguished. Finally we removed the background and calculated the foreground characteristic. The
experimental results show that this approach was effective in improving detection accuracy.
Chunguang Liu, Zhiheng Gong, Huijie Zhu, Yanan Liu, Yue Zhou and Zhonghua Han . (2013). A Novel Human Detection Algorithm Based on Foreground Segmentation.
Journal of Fiber Bioengineering and Informatics. 6 (3).
285-292.
doi:10.3993/jfbi09201306
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