Texture Segmentation in 2D vs. 3D: Did 3D Developmentally Precede 2D?

Texture boundary detection (or segmentation) is an important capability in human vision. Usually, texture segmentation is viewed as a 2D problem, as the definition of the problem itself assumes a 2D substrate. However, an interesting hypothesis emerges when we ask a question regarding the nature of textures: What are textures, and why did the ability to discriminate texture evolve or develop? A possible answer to this question is that textures naturally define physically distinct surfaces, thus, we can hypothesize that 2D texture segmentation may be an outgrowth of the ability to discriminate surfaces in 3D. In this paper, we investigated the relative difficulty of learning to segment textures in 2D vs. 3D configurations. It turns out that learning is faster and more accurate in 3D, very much in line with our expectation. Furthermore, we have shown that the learned ability to segment texture in 3D transfers well into 2D texture segmentation, bolstering our initial hypothesis, and providing a possible explanation for the developmental origin of 2D texture segmentation function in human vision.