A computational model of visual attention. [Dataset]
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CHILUKAMARI, J. 2017. A computational model of visual attention. [Dataset]. Robert Gordon University, PhD thesis.
This dataset is supplementary to the full thesis, which is available on OpenAIR: http://hdl.handle.net/10059/2443. The dataset is compiled of two ZIP files, which will need to be unzipped to access the individual files. The first ZIP file ("Evaluation metrics.zip") contains four MATLAB files in .m format and one plain text README file. The second ZIP file ("Visual Saliency Model (MATLAB).zip") contains seven MATLAB files in .m format, seven image files in .jpg/.jpeg format, three image files in .bmp format and one plain text README file. The abstract for the thesis includes the following extract: This thesis proposes a novel computational model of visual attention that achieves higher prediction accuracy with low computational complexity. A new bottom-up visual attention model based on in-focus regions is proposed. The results show that the model achieves higher prediction accuracy with a lower computational complexity compared to the state-of-the-art visual attention models.
Additional descriptionTwo .zip files, containing 11 .m files, 7 .jpg/.jpeg files, 3.bmp files and 2 .txt files. Created using MATLAB software.See enclosed README files for further description of contents.