Multi-scale Fusion of Texture and Color for Background Modeling

2012 ◽  
Author(s):  
Zhong Zhang ◽  
Chunheng Wang ◽  
Baihua Xiao ◽  
Shuang Liu ◽  
Wen Zhou
Keyword(s):  
Background Modeling ◽  
Multi Scale

Gauss Background Modeling Method Based on Multi-Scale Feature

2013 ◽  
Vol 385-386 ◽  
pp. 1439-1442
Author(s):  
Zhong Hai Li ◽  
Peng Bo Yu ◽  
Qing Cheng Zhang
Keyword(s):  
False Alarm ◽  
Color Vision ◽  
Background Modeling ◽  
Modeling Method ◽  
Experimental Results ◽  
Scale Feature ◽  
Multi Scale ◽  
Single Pixel

The existing background modelings are mostly color vision characteristics modeling based on single pixel, which are easily influenced by light shadow, weather and noise, and can easily cause foreground apertures and false alarm discrete noise. This paper presents the background modeling based on multiscale Gauss parameters against deficiencies. the experimental results shows that it can efficiently solve the problem of cavity and false alarm discrete noise.

scholarly journals ANIMAL DETECTION USING A SERIES OF IMAGES UNDER COMPLEX SHOOTING CONDITIONS

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 249-257 ◽  
Author(s):  
A. G. Zotin ◽  
A. V. Proskurin
Keyword(s):  
Threshold Value ◽  
Saliency Map ◽  
Background Modeling ◽  
Camera Traps ◽  
Multi Scale ◽  
Retinex Algorithm ◽  
In The Wild ◽  
Animal Detection ◽  
Image Collection ◽  
Enormous Number

<p><strong>Abstract.</strong> Camera traps providing enormous number of images during a season help to observe remotely animals in the wild. However, analysis of such image collection manually is impossible. In this research, we develop a method for automatic animal detection based on background modeling of scene under complex shooting. First, we design a fast algorithm for image selection without motions. Second, the images are processed by modified Multi-Scale Retinex algorithm in order to align uneven illumination. Finally, background is subtracted from incoming image using adaptive threshold. A threshold value is adjusted by saliency map, which is calculated using pyramid consisting of the original image and images modified by MSR algorithm. Proposed method allows to achieve high estimators of animals detection.</p>

A Proposal of 3D Feature based on Occupancy of Point Cloud in Multi-Scale Shell Region

2016 ◽  
Vol 136 (8) ◽  
pp. 1078-1084
Author(s):  
Shoichi Takei ◽  
Shuichi Akizuki ◽  
Manabu Hashimoto
Keyword(s):  
Point Cloud ◽  
Multi Scale ◽  
Feature Based ◽  
Shell Region

RECONSTRUCTION OF NON-STATIONARY COMPLEX SPATIAL STRUCTURES BY A NOVEL FILTER-BASED MULTI SCALE MPS ALGORITHM

2014 ◽  
Vol 2014 (2) ◽  
pp. 60-71
Author(s):  
Peyman Mohammadmoradi ◽  
◽  
Mohammad Rasaeii ◽  
Keyword(s):  
Spatial Structures ◽  
Multi Scale
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