scholarly journals Construction of a Visual Saliency Model for Neighborhood Building Landmarks Based on K-Means Clustering

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chen Li ◽  
Zheng Qiao
Keyword(s):  
Influencing Factors ◽  
Linear Regression Analysis ◽  
Quantitative Relationship ◽  
Visual Saliency ◽  
Multiple Linear Regression Analysis ◽  
Detection Algorithm ◽  
Statistical Regression ◽  
Saliency Model ◽  
Visual Index ◽  
Visual Saliency Model

In this paper, firstly, based on the quantitative relationship between K-means clustering and visual saliency of neighborhood building landmarks, the weights occupied by each index of composite visual factors are obtained by using multiple statistical regression methods, and, finally, we try to construct a saliency model of multiple visual index composites and analyze and test the model. As regards decomposition and quantification of visual saliency influencing factors, to describe and quantify these visual significance factors of the landmarks, the significant factors are decomposed into several quantifiable secondary indicators. Considering that the visual saliency of the landmarks in the neighborhood is reflected by the variance of the influencing factors and that the scope of the landmarks is localized, the local outlier detection algorithm is used to solve the variance of the secondary indicators. Since the visual significance of neighborhood building landmarks is influenced by a combination of influencing factors, the overall difference degree of secondary indicators is calculated by K-means clustering. To facilitate the factor calculation, a factor-controlled virtual environment was built to carry out the experimental study of landmark perception and calculate the different degrees of each index of the building. The data of visual indicators of the neighborhood buildings for this experiment were also collected, and the significance values of the neighborhood buildings were calculated. The influence weights of the indicators were obtained by using multiple linear regression analysis, the visual significance model of the landmarks of the neighborhood buildings in the factor-controlled environment was constructed, and the model was analyzed and tested.

scholarly journals Visual Saliency Model-Based Image Watermarking with Laplacian Distribution

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 239
Author(s):  
Hongmei Liu ◽  
Jinhua Liu ◽  
Mingfeng Zhao
Keyword(s):  
Simulation Analysis ◽  
Image Watermarking ◽  
Additive White Gaussian Noise ◽  
Visual Saliency ◽  
High Energy ◽  
Distribution Model ◽  
Saliency Model ◽  
Detection Approach ◽  
Laplacian Distribution ◽  
Visual Saliency Model

To improve the invisibility and robustness of the multiplicative watermarking algorithm, an adaptive image watermarking algorithm is proposed based on the visual saliency model and Laplacian distribution in the wavelet domain. The algorithm designs an adaptive multiplicative watermark strength factor by utilizing the energy aggregation of the high-frequency wavelet sub-band, texture masking and visual saliency characteristics. Then, the image blocks with high-energy are selected as the watermark embedding space to implement the imperceptibility of the watermark. In terms of watermark detection, the Laplacian distribution model is used to model the wavelet coefficients, and a blind watermark detection approach is exploited based on the maximum likelihood scheme. Finally, this paper performs the simulation analysis and comparison of the performance of the proposed algorithm. Experimental results show that the proposed algorithm is robust against additive white Gaussian noise, JPEG compression, median filtering, scaling, rotation attack and other attacks.

A Novel Biologically Inspired Visual Saliency Model

2014 ◽  
Vol 6 (4) ◽  
pp. 841-848 ◽  
Author(s):  
Jingjing Zhao ◽  
Shujin Sun ◽  
Xingtong Liu ◽  
Jixiang Sun ◽  
Afeng Yang
Keyword(s):  
Visual Saliency ◽  
Biologically Inspired ◽  
Saliency Model ◽  
Visual Saliency Model

A Two-Stage Clustering Based 3D Visual Saliency Model for Dynamic Scenarios

2019 ◽  
Vol 21 (4) ◽  
pp. 809-820 ◽  
Author(s):  
You Yang ◽  
Bei Li ◽  
Pian Li ◽  
Qiong Liu
Keyword(s):  
Visual Saliency ◽  
Two Stage ◽  
Saliency Model ◽  
Visual Saliency Model

Local and Global Contrast for Saliency Estimate in DCT Domain

2013 ◽  
Vol 456 ◽  
pp. 611-615
Author(s):  
Nan Ping Ling ◽  
Han Ling Zhang
Keyword(s):  
State Of The Art ◽  
Visual Saliency ◽  
Local Contrast ◽  
Global Contrast ◽  
Contrast Method ◽  
Saliency Model ◽  
Dct Domain ◽  
Proposed Model ◽  
Roc Area ◽  
Visual Saliency Model

In this paper, we present a new bottom-up visual saliency model, which utilizes local and global contrast method to calculate the saliency in DCT domain. Our proposed method is firstly used in the DCT domain. The local contrast method uses the center-surround operation to compute the local saliency, and the global contrast method calculate the dissimilarity between DCT blocks of image and any other DCT blocks in any location. The final saliency is generated by combining the local with global contrast saliency. Experimental evaluation on a publicly available benchmark dataset shows the proposed model can acquire state-of-the-art results and outperform the other models in terms of the ROC area.

scholarly journals QSAR Analysis of 5-Substituted-2-Benzoyl-aminobenzoic acids as PPAR Modulator

2004 ◽  
Vol 1 (5) ◽  
pp. 243-250 ◽  
Author(s):  
R. Hemalatha ◽  
L. K. Soni ◽  
A. K. Gupta ◽  
S. G. Kaskhedikar
Keyword(s):  
Linear Regression Analysis ◽  
Qsar Model ◽  
Multiple Linear Regression Analysis ◽  
Quantitative Structure Activity Relationship ◽  
Statistical Regression ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Aminobenzoic Acids ◽  
Leave One Out ◽  
Α Activity

A quantitative structure activity relationship (QSAR) study on a series of analogs of 5-aryl thiazolidine-2, 4-diones with activity on PPAR-α and PPAR-γwas made using combination of various thermodynamic, electronic and spatial descriptors. Several statistical regression expressions were obtained using multiple linear regression analysis. The best QSAR model was further validated by leave one out cross validation method. The studied revealed that for dual PPAR-α/γactivity dipole-dipole energy and PMI-Z play significant role and contributed positively for PPAR-γand PPAR-α activity respectively. Thus, QSAR brings important structural insight to aid the design of dual PPAR-α /γreceptor agonist.

A Saliency Detection Method Based on Wavelet Transform and Simple Priors

2014 ◽  
Vol 602-605 ◽  
pp. 2238-2241
Author(s):  
Jian Kun Chen ◽  
Zhi Wei Kang
Keyword(s):  
Wavelet Transform ◽  
Detection Method ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Feature Maps ◽  
Multi Scale ◽  
Saliency Model ◽  
Proposed Model ◽  
Visual Saliency Model ◽  
Better Than

In this paper, we present a new visual saliency model, which based on Wavelet Transform and simple Priors. Firstly, we create multi-scale feature maps to represent different features from edge to texture in wavelet transform. Then we modulate local saliency at a location and its global saliency, combine the local saliency and global saliency to generate a new saliency .Finally, the final saliency is generated by combining the new saliency and two simple priors (color prior an location prior). Experimental evaluation shows the proposed model can achieve state-of-the-art results and better than the other models on a public available benchmark dataset.

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