{'fraction_non_alphanumeric': 0.016564417177914112, 'fraction_numerical': 0.0, 'mean_word_length': 4.9963235294117645, '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}}
A probabilistic approach for the reconstruction of polyhedral objects using shape from shading technique

There are many objects in the real world, especially, man made objects often having a polyhedral shape. Shape from shading (SFS) is a well known and the most robust technique of Computer vision. SFS is a first order nonlinear, ill-posed problem. The main idea for solving ill-posed problems is to restrict the class of admissible solution by introducing suitable a priori knowledge. To overcome the ill-posedness in SFS techniques, Bayesian estimation of geometrical constraints are used. The Lambertian reflectance model is used in this method due to its wide applicability in SFS techniques. The priori or the constraints are represented in the form of probability distribution function, so that the Bayesian approach can be applied. The Monte Carlo method is applied for generating the sample fields from the distribution so that the model can represent our priori knowledge and constraints. The optimal estimators are also computed by using Monte Carlo method. The geometric constraints for lines and planes are used in probabilistic manner to eliminate the rank deficiency to get the unique solution. In case of incorrect line drawings, it is not always possible to reconstruct the object shape uniquely. To deal with this problem, we have processed each planar face separately. Hence, the proposed method is applicable in case of slight error in computation of vertex positions in the images of polyhedral objects. The proposed method is used on various synthetic and real images and satisfactory results are obtained.