scholarly journals An efficient visual saliency detection model based on Ripplet transform

Sadhana ◽  
2017 ◽  
Vol 42 (5) ◽  
pp. 671-685 ◽  
Author(s):  
A Diana Andrushia ◽  
R Thangarajan
Keyword(s):  
Saliency Detection ◽  
Visual Saliency ◽  
Ripplet Transform ◽  
Detection Model ◽  
Model Based ◽  
Visual Saliency Detection

scholarly journals SAMM: Surroundedness and Absorption Markov Model Based Visual Saliency Detection in Images

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 71422-71434 ◽  
Author(s):  
Zhenguo Gao ◽  
Naeem Ayoub ◽  
Danjie Chen ◽  
Bingcai Chen ◽  
Zhimao Lu
Keyword(s):  
Markov Model ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Model Based ◽  
Visual Saliency Detection

3D visual saliency detection model with generated disparity map

2016 ◽  
Vol 76 (2) ◽  
pp. 3087-3103 ◽  
Author(s):  
Feng Qi ◽  
Debin Zhao ◽  
Shaohui Liu ◽  
Xiaopeng Fan
Keyword(s):  
Saliency Detection ◽  
Visual Saliency ◽  
Disparity Map ◽  
Detection Model ◽  
Visual Saliency Detection

Unsupervised visual saliency detection via information content measuring

2012 ◽  
Vol 48 (25) ◽  
pp. 1591-1593 ◽  
Author(s):  
Di Wu ◽  
Xiudong Sun ◽  
Yongyuan Jiang ◽  
Chunfeng Hou
Keyword(s):  
Information Content ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Visual Saliency Detection

A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors

2019 ◽  
Vol 9 (3) ◽  
pp. 23-37
Author(s):  
Monika Singh ◽  
Anand Singh Singh Jalal ◽  
Ruchira Manke ◽  
Aamir Khan
Keyword(s):  
Minimum Distance ◽  
Saliency Detection ◽  
Visual Saliency ◽  
Research Area ◽  
Experimental Results ◽  
Low Level ◽  
Detection Approach ◽  
Art Methods ◽  
High Level ◽  
Visual Saliency Detection

Saliency detection has always been a challenging and interesting research area for researchers. The existing methodologies either focus on foreground regions or background regions of an image by computing low-level features. However, considering only low-level features did not produce worthy results. In this paper, low-level features, which are extracted using super pixels, are embodied with high-level priors. The background features are assumed as the low-level prior due to the similarity in the background areas and boundary of an image which are interconnected and have minimum distance in between them. High-level priors such as location, color, and semantic prior are incorporated with low-level prior to spotlight the salient area in the image. The experimental results illustrate that the proposed approach outperform the sate-of-the-art methods.

scholarly journals A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 121330-121343
Author(s):  
Alessandro Bruno ◽  
Francesco Gugliuzza ◽  
Roberto Pirrone ◽  
Edoardo Ardizzone
Keyword(s):  
Saliency Detection ◽  
Visual Saliency ◽  
Multi Scale ◽  
Visual Saliency Detection
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