Person Identification with Tracking System for Indoor Surveillance Using Multiple Top-view Depth Cameras
Date Issued
2014
Date
2014
Author(s)
Hsiao, Po-Hao
Abstract
In this thesis, we propose a novel person identification system, hoping to
identify members at indoor environment by using the biological feature
obtained by top-view depth camera. In the beginning, we do the background
subtraction from the original depth information image and get the
foreground object. After extracting the foreground image we will use a
simple mapping function from camera coordinate to the world coordinate. A
top-view human detector is used to understand which foreground object is
really human. The SVM classifier will be applied to identify people after the
detection process. In the end, the SIR particle filter will be utilized to track
the human. There are three advantages of our framework: 1) the detector
can pick up true human shape in real-time which can make our identification
process more effective, 2) our proposed person identification system can
simultaneously identify multiple people in the same time, 3) according to the
addition of the tracker, we can tolerate height variation and human shape
distortion. At last, in the experimental results, we use the confusion matrix
to evaluate effectiveness of our person identification process, and
successfully validates the accuracy of the system.
identify members at indoor environment by using the biological feature
obtained by top-view depth camera. In the beginning, we do the background
subtraction from the original depth information image and get the
foreground object. After extracting the foreground image we will use a
simple mapping function from camera coordinate to the world coordinate. A
top-view human detector is used to understand which foreground object is
really human. The SVM classifier will be applied to identify people after the
detection process. In the end, the SIR particle filter will be utilized to track
the human. There are three advantages of our framework: 1) the detector
can pick up true human shape in real-time which can make our identification
process more effective, 2) our proposed person identification system can
simultaneously identify multiple people in the same time, 3) according to the
addition of the tracker, we can tolerate height variation and human shape
distortion. At last, in the experimental results, we use the confusion matrix
to evaluate effectiveness of our person identification process, and
successfully validates the accuracy of the system.
Subjects
人員識別
生物特徵
粒子濾波器
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-103-R01921013-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):f812801eff8b07c4d5a401fd3a2d68c5