Quantitative Evaluation of Hair Texture

In this paper, we quantitatively evaluate the role of texture in hair patches, with a primary motivation of understanding what can be learned and applied by machine learning systems for texture-based hair detection. We evaluate the distribution of gradient directions in hair patches, and explore the relation between proximity to the face and the angle of the gradients for 2,870,000 hair patches selected from 100 manually silhouetted hairstyles.