Asymmetric Low Spatial Frequency Improves Face Discrimination

本實驗的目的在於理解人類視覺系統如何從陰影的訊息中建構臉部的立體訊息。我們利用電腦軟體改變投射在3D立體臉部模型的光影變化，然後記錄觀察者對於臉部辨識作業如何隨著照明方向改變而有所不同。我們使用對稱性算則分離臉部影像的照明與臉部的表面特質。我們一共區分了對稱與不對稱的低空間頻率和高空間頻率的四種成分。實驗刺激是這些不同成份的組成。結果顯示非對稱低空間頻率成分，亦即陰影訊息會顯著改變臉部辨識。然而，對稱的低空間頻率成分卻對臉部辨識沒有影響。此外；非對稱低空間頻率也會改變臉部影像的深度知覺。總結以上結果 可以確定的是非對稱低空間頻率訊息決定了臉部的特性以及深度知覺。而且這個效果隨著照明光源角度的改變而有所不同。所以，我們的結果支持視覺系統中以立體維度來處理臉部辨識的訊息。To study how the visual system compute 3D shape of faces from shading information, we manipulated the illumination conditions on 3D scanned face models and observed how the face discrimination changes with lighting directions . We used a symmetry algorithm to dissociate surface albedo and illumination component of face images by separating symmetric and asymmetric components of both low and high spatial frequency information of face images. Stimuli were hybrid faces with different combination of symmetric and spatial content. Results show that asymmetric low spatial frequency (shading) information had significant influence on face discrimination, while the symmetric ones have little, if any, effect on face discrimination. The asymmetric low spatial frequency also changed the perceived depth of hybrid faces. Together, these results suggest that (1) the asymmetric low spatial frequency information dramatically affects both perceived face identity and perceived depth; and (2) this effect increased as the lighting direction shifts to the side. Thus, our results provide an evidence for 3D-based face processing