Shape depiction using Local Light Alignment : Evaluating the shape enhancement capabilities of the Local Light Alignment technique at multiple scales

Sammanfattning: Local Light Alignment is a new shading based technique in the field of shape depiction, a field which concerns itself with techniques to represent and enhance the three-dimensional (3D) shape of objects in two-dimensional (2D) visual media. The main idea of Local Light Alignment is to locally adjust the incoming direction of light to create contrast in a way that enhances the perception of shape and surface detail. It is aimed at visual artists and uses a multiple scale approach, where the user can tune the enhancement of geometric shapes of different sizes. Local Light Alignment was published together with a new objective metric for measuring shape depiction called the congruence score. This thesis strives to increase knowledge about both these new techniques by investigating how varying several parameters for Local Light Alignment affect the congruence score at different scales and strengths of enhancement. The parameters investigated are the range and spatial parameters for the bilateral filter in the scale space construction as well as the enhancement strength parameter of the main Local Light Alignment algorithm. The thesis also tries to identify any common visual characteristics for images that score high, to give a better intuition of what the congruence score represents. The tests are performed using four models, each representing a different field of application. For each model, several viewpoints are tested, and for every viewpoint, 244 differently parameterized renders are produced and scored. The results notably show that the spatial and range parameters both affect controllability of the algorithm by shifting the scores toward the finer end of the scale space with higher values, without affecting the total score. The enhancement strength parameter is shown to affect the congruence score positively, but with diminishing returns as values approach 1. It is also shown by example that the images showing the largest improvement in congruence score tend to exhibit such high degrees of exaggeration that they would probably not be considered good examples of shape depiction by human standards. This is identified as an interesting area to perform subjective evaluations in future research. These investigations will be valuable to those who will create application software that features Local Light Alignment, as well as those wanting to employ the congruence score metric.