Authors
Chunyu Yu, Fengzhi Dai
Corresponding Author
Fengzhi Dai
Available Online 1 September 2016.
DOI
https://doi.org/10.2991/jrnal.2016.3.2.7
Keywords
Mobile cameras, motion segmentation, edge-based alignment, object detection.
Abstract
The need of detecting moving object like human and vehicle by mobile camera
is increasing in commerce and industry. Therefore, tradition method of
abstracting moving object from still background cannot solve the problem.
Though Histogram of Oriented Gradients (HOG) have been widely used for
human detection, due to relying on sliding windows and multi-scale resizing
method, it is computational expensive to perform on ordinary equipment.
In this paper, an image-resize methodology which can abstract motion segmentation
and detect moving object from moving background is proposed. First, edges
images are computed. Then movement vector between frame images are computed
and the relative background motion is compensated. By adjusting the parameters
of resize algorithm, human liked object or vehicle liked object can be
segmented separately and the segmentation can be used for further detection.
Experiments have been performed under three different environments for
human detection and vehicle detection. The results show that the running
time is highly reduced and the accuracy can reach as high as 93.04%.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).