IIIT Hyderabad Publications |
|||||||||
|
Empirical and Computational Investigation of Aesthetic AttributesAuthor: Gautam Kumar Malu Date: 2019-01-28 Report no: IIIT/TH/2019/18 Advisor:Bipin Indurkhya,Bapi Raju Surampudi AbstractAesthetics is the study of the science behind the concept and perception of beauty. Psychologists have long been studying it via various experiments, which is called as experimental aesthetics. Aesthetic attributes are a set of universal principles to create aesthetically pleasing art objects, based on human’s visual processing. These attributes are taught as basic design principles, for example visual balance, color harmony, etc. In this thesis, we investigate the perception of visual balance in abstract black and white and colored paintings with experiments with university students. Visual balance is defined as a certain arrangement of the elements in a picture with respect to the canvas and with respect to each other, the point at which the composition appears more stable and coherent. We derive an objective measurement of visual balance based on the center of visual weight. The visual weight of an element is the attention-pull that element exerts on the viewer. We later synthesize an approach for optimal text placement over images using the same objective measurement and validate the results with user studies. With advancement in computer vision and Machine Learning, there have been many attempts to model the aesthetics especially in paintings, and photographs [42, 23, 71]. In this thesis, we also model eight different aesthetic attributes via a multi-task deep convolution network and derive state of art results on AADB dataset [28]. We also visualize these aesthetic attributes via gradient based technique and discuss the different level of complexity associated with different attributes. Full thesis: pdf Centre for Cognitive Science |
||||||||
Copyright © 2009 - IIIT Hyderabad. All Rights Reserved. |