{'fraction_non_alphanumeric': 0.013924050632911392, 'fraction_numerical': 0.0, 'mean_word_length': 5.084615384615384, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
D Model Acquisition Including Reflection Properties

The measurement of accurate material properties is an important step towards the inclusion of realistic objects in digital documents. Many real-world objects are composed of a number of materials with subtle changes even within a single material. We present an image-based measuring method that robustly detects the different materials of real objects and fits an average bidirectional reflectance distribution function (BRDF) to each of them. In order to model the local changes as well, we project the measured data for each surface point into a basis formed by the recovered BRDFs leading to a truly spatially varying BRDF representation. A compact, high quality model of a real object can be generated with relatively few input data.