Project 3: Artifact

CSEP 576, Winter 2005
Biliana Kaneva

Dataset: Buddha

RGB-encoded Normals	Needle Map
Albedo Map
View 1: No Albedo Mapping	View 2: No Albedo Mapping
View 1: Albedo Mapping	View 2: Albedo Mapping

Dataset: Cat

RGB-encoded Normals	Needle Map
Albedo Map
View 1: No Albedo Mapping	View 2: No Albedo Mapping
View 1: Albedo Mapping	View 2: Albedo Mapping

Dataset: Owl

RGB-encoded Normals	Needle Map
Albedo Map
View 1: No Albedo Mapping	View 2: No Albedo Mapping
View 1: Albedo Mapping	View 2: Albedo Mapping

Results Discussion

The reconstructions worked more or less identically to the sample solution. The lightning directions generated by my solution were a little bit off, but the difference was less than .002. The difference was insignificant with respect to the final result. I also had a bit of hard time chasing a bug when computing the depth because of NaNs in the normals. Once I removed those, everything worked perfectly.

I think the results were quite good even though this approach has some limitations. The one dataset that was very poorly reconstructed was the gray sphere. The stand of the sphere was not illuminated very well, so the only part that was reconstructed was the sphere itself. The owl dataset had a slight problem with the eyes (notice the side view of the owl). I guess this is due to the fact that normals estimate is not good in the areas of dark pixels. One way to solve/improve this is to use a measure of confidence by weighing the contsraints for dark pixels less havily than the constraints for bright pixels as described in the Bells & Whistles section of the project. Unfortunately, I didn't have a chance to implement any of the extra credit suggestions.

Other limitations of this method of reconstruction are related to the fact that the method is based on the assumption that the object has a Lambertian surface and it also requires lighting calibration using a chrome sphere in the scene which can be somewhat cumbersone. One way to perhaps create the illusion of a surface being diffuse is using low-intensity lighting, so that to reduce the chances of specular highlights. Of course, we have to be careful that the object is not too dark, otherwise the normal estimates will not be good.