Cast shadow removal in motion detection by exploiting multiview geometry

Author(s):  
Ming Xu ◽  
Lei Lu ◽  
Tianyuan Jia ◽  
Jie Ren ◽  
Jeremy S. Smith
2007 ◽  
Author(s):  
Guilin Zhang ◽  
Ying Chu ◽  
Song Tian ◽  
Yufei Zha ◽  
Gengming Zhu

2014 ◽  
Vol 644-650 ◽  
pp. 1066-1069
Author(s):  
Dong Mei Zhou ◽  
Ming Xing Zhang ◽  
Yong Xia Dai

Based on the research and analysis of video sequence of the Intelligent Transport Systems,this paper especially had a in-depth discussion about the critical step of video detection—shadow removing, analyzing the causes and characteristics of the shadow,describing the current shadow removal algorithms,and proposed a new method of image texture-based vehicle cast shadow elimination approach based on the existing algorithms.Experimental results have proved that this method can remove the vehicle shadow well and still hold very complete target vehicle information and laid the foundation for extracting vehicle target.


2013 ◽  
Vol 7 (4) ◽  
pp. 695-703 ◽  
Author(s):  
Chu Tang ◽  
M. Omair Ahmad ◽  
Chunyan Wang

2014 ◽  
Vol 602-605 ◽  
pp. 1778-1781
Author(s):  
Hong Cheng Zhou ◽  
Zhi Peng Jiang

Focusing on the disturbance of moving cast shadow, a Bagging-ensemble-based moving cast shadow removal method is proposed. Collecting shadow discrimination features from multiple shadow discrimination models, a shadow detector is trained by employing Bagging ensemble based learning framework. The shadow detector can automatically select effective shadow discrimination features and be updated online adaptively. Experimental results demonstrate the effectiveness of the proposed method.


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