I took interest in this study done on splitting specular and diffuse with real images and wanted to incorporate it into my typology machine.
Goal
As the diagram above shows, I want to create a system where I have a collection of photos and a model of the object, and it outputs 3d capture of the object with its respective material properly mapped.
Due to my lack of knowledge in ML, I feel like it would be difficult to expect the system to do the mapping on its own. As in, I initially want the system to distinguish from the photos 1. the object is composed of how many different parts and 2. which material property matches with which respective parts. However, this process might need to be done manually.
Target Object
What I really wanted to explore in this study is how can I capture an object composed of different components. Most real objects are made up of different parts with different material properties. Using the scissor example, the blade will have a higher specular value than the handle because it is more shiny and bounces off more specular light.
Therefore, for my subject of capture I wanted to work with my lotion bottles, which has a mix of different material types.
