Department of Computer Engineering
Perceptually-Driven Computer Graphics and Visualization
(Supervisor: Prof. Dr. Bülent Özgüç)
Computer Engineering Department
In the last decade, utilization of visual perception findings in computer graphics has started to get popular since visual quality is actually judged by the human perception and there is no need to spend additional cost for the physical realism of the details that cannot be perceived by the observer. We contribute to the perceptual computer graphics research in two main aspects: First we propose several perceptual error metrics for evaluating the visual quality of 3D meshes. Second, we develop a system for ameliorating the perceived depth quality and comprehensibility in 3D visualization applications.
A measure for assessing the quality of a 3D mesh is necessary in order to determine whether an operation on the mesh, such as watermarking or compression, affects the perceived quality. A bottom-up approach incorporating both the spatial and temporal components of the low-level human visual system processes is suggested for a general-purpose quality metric to measure the local distortion visibility on dynamic triangle meshes. In addition, utilization of crowdsourcing and machine learning methods to implement a novel data-driven error metric for 3D models is also demonstrated.
During the visualization of 3D content, using the depth cues selectively to support the design goals and enabling a user to perceive the spatial relationships between the objects are important concerns. In this regard, a framework for selecting proper depth cues and rendering methods providing these cues for the given scene and visualization task is put forward. This framework benefits from fuzzy logic for determining the importance of depth cues and knapsack method for modeling the cost-profit tradeoff between the rendering costs of the methods and their contribution to depth perception.
All the proposed methods in this study are validated through formal user experiments and we obtain encouraging results for further research. These results are made publicly available for the benefit of graphics community. In conclusion, we try to make the gap between visual perception and computer graphics fields narrower with the suggested methods.
DATE: 13 October, 2016, Thursday @ 10:30