A region covariances-based visual attention model for RGB-D images
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2016, Vol 4, Issue 4
Abstract
Existing computational models of visual attention generally employ simple image features such as color, intensity or orientation to generate a saliency map which highlights the image parts that attract human attention. Interestingly, most of these models do not process any depth information and operate only on standard two-dimensional RGB images. On the other hand, depth processing through stereo vision is a key characteristics of the human visual system. In line with this observation, in this study, we propose to extend two state-of-the-art static saliency models that depend on region covariances to process additional depth information available in RGB-D images. We evaluate our proposed models on NUS-3D benchmark dataset by taking into account different evaluation metrics. Our results reveal that using the additional depth information improves the saliency prediction in a statistically significant manner, giving more accurate saliency maps.
Authors and Affiliations
Erkut Erdem*| Hacettepe University. Department of Computer Engineering, Ankara, Turkey – TR-06800
Keywords
Related Articles
- EP ID EP811
- DOI 10.18201/ijisae.2016426384
- Views 478
- Downloads 25
Application of Angle-Modulated Particle Swarm Optimization Technique in Power System Controlled Separation WAP
One of the recommended preventive plans against the wide area disturbances is WAP, Wide Area Protection, through controlled system splitting or separation. In this paper, authors are proposing three simple algorithms tha...
Preferences, Utility and Prescriptive Decision Control in Complex Systems
The evaluation of the preferences based utility function is a goal of the human cantered control (management) design.The achievement of this goal depends on the determination and on the presentation of the requirements,...
New Approach in E-mail Based Text Steganography
In this study combination of lossless compression techniques and Vigenere cipher was used in text steganography that makes use of email addresses to be the keys to reconstruct the secret message which has been embedded i...
Statistical Methods for Quantitatively Detecting Fungal Disease from Fruits’ Images
In this paper we have proposed statistical methods for detecting fungal disease and classifying based on disease severity levels. Most fruits diseases are caused by bacteria, fungi, virus, etc of which fungi are respons...
Artificial Neural Network Models for Predicting the Energy Consumption of the Process of Crystallization Syrup in Konya Sugar Factory
In this study, artificial neural network models have been developed from the sugar production process stages in Konya Sugar Factory using artificial neural networks to estimate the energy consumption of the process of cr...