Physics-based vision is a methodological paradigm within computer vision that employs explicit physical models to analyze and interpret image data. It investigates the complex interplay between illumination, material properties, and geometric structure, seeking to infer quantitative scene characteristics by modeling the image formation process. This approach provides a robust framework for understanding image content beyond simple pattern recognition, enabling the measurement of physical attributes and prediction of appearance under varying conditions.