Summary
Texture analysis in portraits did not distinguish likeness, unlike shape analysis. Findings suggest lighting and shape-texture interactions influence perceived likeness in portraiture.
Area of Science:
- Computer Vision and Image Analysis
- Art History and Perception
Background:
- Previous research (companion paper) utilized principal component analysis (PCA) on portrait shape to assess likeness.
- This study investigates the role of texture in perceived portrait likeness, comparing it to shape-based assessments.
Purpose of the Study:
- To explore the relationship between texture depiction in portraits and perceived likeness.
- To determine if texture-based principal component analysis (PCA) can differentiate between high and low likeness portraits.
Main Methods:
- Principal component analysis (PCA) applied to portrait texture features.
- Experimentation with various pre-processing techniques to manage image-level texture variability.
- Analysis of lighting direction, histogram matching, and shape-texture relationships.
Main Results:
- Texture PCA failed to discriminate between high and low likeness portraits, even after pre-processing.
- Linear histogram matching effectively reduced portrait brightness variability.
- Depicting or exaggerating shading related to lighting direction may enhance likeness; lighting direction can be portrayed anomalously.
- Shape and texture were found to be interdependent, not independent variables.
Conclusions:
- Texture, unlike shape, did not prove to be a reliable predictor of perceived likeness in this portrait set.
- Image registration methods, while useful, may confound texture PCA results under ambient conditions.
- Further research is needed to understand the complex interplay of shape, texture, and lighting in portrait perception.
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