NESP TWQ Round 3 - Project 3.2.3 - Monitoring aesthetic value of the GBR by using artificial intelligence to score photos and videos
This project addresses the urgent need to understand and monitor the aesthetic value of the Great Barrier Reef. Focusing on the fast-changing underwater systems of the Reef, this research used advanced technology (including eye tracking and heart rate measurement) to elicit what environmental and experiential attributes contribute to aesthetic value. A Big Data platform using artificial intelligence was created to assess large volumes of visitor supplied imagery and to map aesthetic value across space and time.
More details about this project can be found on the Monitoring the Great Barrier Reef Griffith Inititue for Tourism website.
This project is continuing under NESP TWQ Round 5 - Project 5.5 – Measuring aesthetic and experience values using Big Data approaches
Videos
Datasets
The last stream within the NESP 5.5 project was related to the conduct of an online survey to get aesthetic ratings of additional 3500 images downloaded from Flickr to improve the Artificial Intelligence (AI)-based system recognising and assessing the beauty of natural scenes, which had been developed in the previous NESP 3.2.3 project. Despite some earlier investment into this research area, there is still a need to improve the tools we use to measure the aesthetic beauty of marine landscapes.
The second stream within the NESP 5.5 project was conducted using eye-tracking technology to examine possible differences between three participant groups in evaluating the aesthetic beauty of GBR underwater sceneries. This research continue the efforts initiated in the previous NESP 3.2.3 project to explore the power of eye-tracking as an objective measure of human aesthetic assessment of GBR underwater sceneries.
Organizing focus groups was used as an effective qualitative research method to examine collective opinions of participants on a specific topic. Within NESP 5.5 project, focus groups consist of an exploratory study to explore the psychological antecedents of human aesthetic assessment of underwater sceneries at the GBR among three groups of different cultural backgrounds: Chinese, non-indigenous Australians and First People Australians. Focus group folder contains one dataset report, and three folders (Australian, Chinese, First People) with seven images.
Methods:
This dataset contains the caffe deep-learning framework along with the setup for image aesthetic train and test code for the Algorithm data. We used NVIDIA-digit 6 environment and this version use caffe 0.15.14 More details information can be found in http://caffe.berkeleyvision.org.
This dataset consists of three data folders for the eye-tracking experiment conducted within the NESP 3.2.3 project (Tropical Water Quality Hub): Folder (1) The folder of Eye-tracking videos contains 66 Tobii recordings of participants’ eye movements on screen, Folder (2) The Heatmaps folder includes 21 heatmaps created by Tobii eye-tracking software on the basis of 66 participants’ data and Folder (3) The input folder has 21 original pictures used in eye-tracking experiment.