中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
地理科学与资源研究所 [2]
长春光学精密机械与物... [2]
计算技术研究所 [1]
心理研究所 [1]
中国科学院大学 [1]
采集方式
OAI收割 [6]
iSwitch采集 [1]
内容类型
期刊论文 [5]
会议论文 [2]
发表日期
2020 [2]
2013 [1]
2011 [2]
2006 [2]
学科主题
Cognitive ... [1]
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Value capturecapture mechanisms, transaction costs, and heritage conservation: A case study of Sanjiangyuan National Park, China
期刊论文
OAI收割
LAND USE POLICY, 2020, 卷号: 90, 页码: 12
作者:
Wu, Jiayu
;
Wu, Gefei
;
Zheng, Tianli
;
Zhang, Xiaobin
;
Zhou, Kan
  |  
收藏
  |  
浏览/下载:45/0
  |  
提交时间:2020/05/19
Value capture
Protected area
Transaction cost
Ecological compensation
Ecological migration
Value capturecapture mechanisms, transaction costs, and heritage conservation: A case study of Sanjiangyuan National Park, China
期刊论文
OAI收割
LAND USE POLICY, 2020, 卷号: 90, 页码: 12
作者:
Wu, Jiayu
;
Wu, Gefei
;
Zheng, Tianli
;
Zhang, Xiaobin
;
Zhou, Kan
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2020/05/19
Value capture
Protected area
Transaction cost
Ecological compensation
Ecological migration
Contingent capture can occur at specific feature values: Behavioral and electrophysiological evidence
期刊论文
OAI收割
BIOLOGICAL PSYCHOLOGY, 2013, 卷号: 92, 期号: 2, 页码: 125-134
作者:
Jiao, Jun
;
Zhao, Guang
;
Wang, Qi
;
Zhang, Kan
;
Li, Hong
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2015/05/19
Attentional capture
Top-down control
Specific feature value
N2pc effect
The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE)
会议论文
OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者:
Sun H.
;
Han H.-X.
;
Sun H.
收藏
  |  
浏览/下载:57/0
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提交时间:2013/03/25
Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring
precision
and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection
the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure
but in order to capture the change of the state space
it need a certain amount of particles to ensure samples is enough
and this number will increase in accompany with dimension and increase exponentially
this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining"
we expand the classic Mean Shift tracking framework.Based on the previous perspective
we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis
Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism
used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation
and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information
this approach also inhibit interference from the background
ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE)
会议论文
OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者:
Dong Y.-X.
;
Zhang H.-B.
;
Li Y.
;
Li Y.
;
Li Y.
收藏
  |  
浏览/下载:109/0
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提交时间:2013/03/25
Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system
the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms
such as adaptive background prediction detecting method. When background has dispersion-decreasing structure
the traditional target detection algorithms would be more useful. But when the background has large gray gradient
such as sea-sky-line
sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature
in our opinion
from the perspective of mathematics
the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis
the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection
its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore
the purpose of the image preprocessing is to reduce the effects from noise
also to raise the SNR of image
and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics
the median filter is used to eliminate noise
improve signal-to-noise ratio
then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line
so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Least-squares fitting of multiple m-dimensional point sets
期刊论文
iSwitch采集
Visual computer, 2006, 卷号: 22, 期号: 6, 页码: 387-398
作者:
Wen, GJ
;
Wang, ZQ
;
Xia, SH
;
Zhu, DM
收藏
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浏览/下载:28/0
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提交时间:2019/05/10
Absolute orientation
Least-squares fitting
Singular value decomposition
Motion capture
Least-squares fitting of multiple M-dimensional point sets
期刊论文
OAI收割
VISUAL COMPUTER, 2006, 卷号: 22, 期号: 6, 页码: 387-398
作者:
Wen, GJ
;
Wang, ZQ
  |  
收藏
  |  
浏览/下载:13/0
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提交时间:2019/12/16
absolute orientation
least-squares fitting
singular value decomposition
motion capture