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CAS IR Grid
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长春光学精密机械与物... [2]
计算技术研究所 [1]
自动化研究所 [1]
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OAI收割 [4]
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会议论文 [2]
期刊论文 [2]
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2015 [1]
2014 [1]
2011 [1]
2006 [1]
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A Benchmark and Comparative Study of Video-Based Face Recognition on COX Face Database
期刊论文
OAI收割
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 卷号: 24, 期号: 12, 页码: 15
作者:
Huang, Zhiwu
;
Shan, Shiguang
;
Wang, Ruiping
;
Zhang, Haihong
;
Lao, Shihong
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2019/12/13
Video-based face recognition
video-to-still
still-to-video
video-to-video
COX Face DB
benchmarking
point-to-set correlation learning
Point-Manifold Discriminant Analysis for Still-to-Video Face Recognition
期刊论文
OAI收割
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2014, 卷号: E97D, 期号: 10, 页码: 2780-2789
作者:
Chen, Xue
;
Wang, Chunheng
;
Xiao, Baihua
;
Shao, Yunxue
收藏
  |  
浏览/下载:32/0
  |  
提交时间:2015/08/12
face recognition
still-to-video
discriminant analysis
point-manifold distance
scenario-oriented
Precise motion compensation based on weighted sub-pixel image matching (EI CONFERENCE)
会议论文
OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Liang H. G.
收藏
  |  
浏览/下载:25/0
  |  
提交时间:2013/03/25
This paper proposed a sub-pixel image correlation algorithm that can get more Precise result
its principle is apply the distribute of relativity peak to get weighted multi-pixel comprehensive of location. Image correlation be as to calculates the greyscale relativity of image template and matching image
the relativity of correspond location where match best with template will be most high
and in its neighbour range
the relativity will be still keep high too. We used these pixel in this local area of calculated match point to get sub-pixel accuracy
the relativity of every pixel be used as its weight for participate the sub-pixel calculation. The sub-pixel location is more accuracy than the integer one
we applied this method to perform background compensation in processing the target detecting for video image sequence. At the end of this paper
some experiment data be proposed
it proved this sub-pixel image correlation can obtain better result. 2011 SPIE.
High-accuracy real-time automatic thresholding for centroid tracker (EI CONFERENCE)
会议论文
OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:
Wang Y.
;
Wang Y.
;
Wang Y.
;
Wang Y.
收藏
  |  
浏览/下载:37/0
  |  
提交时间:2013/03/25
Many of the video image trackers today use the centroid as the tracking point. In engineering
we can get several key pairs of peaks which can include the target and the background around it and use the method of Otsu to get intensity thresholds from them. According to the thresholds
it give a great help for us to get a glancing size
a target's centroid is computed from a binary image to reduce the processing time. Hence thresholding of gray level image to binary image is a decisive step in centroid tracking. How to choose the feat thresholds in clutter is still an intractability problem unsolved today. This paper introduces a high-accuracy real-time automatic thresholding method for centroid tracker. It works well for variety types of target tracking in clutter. The core of this method is to get the entire information contained in the histogram
we can gain the binary image and get the centroid from it. To track the target
so that we can compare the size of the object in the current frame with the former. If the change is little
such as the number of the peaks
the paper also suggests subjoining an eyeshot-window
we consider the object has been tracked well. Otherwise
their height
just like our eyes focus on a target
if the change is bigger than usual
position and other properties in the histogram. Combine with this histogram analysis
we will not miss it unless it is out of our eyeshot
we should analyze the inflection in the histogram to find out what happened to the object. In general
the impression will help us to extract the target in clutter and track it and we will wait its emergence since it has been covered. To obtain the impression
what we have to do is turning the analysis into codes for the tracker to determine a feat threshold. The paper will show the steps in detail. The paper also discusses the hardware architecture which can meet the speed requirement.
the paper offers a idea comes from the method of Snakes