{'fraction_non_alphanumeric': 0.006674082313681869, 'fraction_numerical': 0.0, 'mean_word_length': 5.338028169014085, '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}}
Robustness Improvement in Optical Deformation Analysis by Matching a Motion Field to Stress Imposed on a Surface

A denoizing and compression method for motion field data is proposed to improve the robustness and efficiency of optical deformation analysis. The proposed method estimates stress change over time imposed on a captured surface based on displacements and strains derived from motion fields obtained by optical flow. The method then finds the best least squares approximation of the motion components due to the stress time series from the motion time series at each coordinate. This process decomposes motion fields into stress and response vectors while removing disturbances. Experimental results confirm that the proposed method significantly reduces noise in visualizing crack opening displacements on a bridge beam under traffic loads, as well as the size of the motion field data.