{'fraction_non_alphanumeric': 0.020348837209302327, 'fraction_numerical': 0.0017441860465116279, 'mean_word_length': 6.200836820083682, '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}}
Effective 3D Geometric Matching for Data Restoration and Its Forensic Application

3D matching is a fundamental and important technique that detects and aligns repeated or similar patterns between geometric objects. It can facilitate many data processing and analysis tasks in computer graphics and vision, including shape comparison and retrieval, data fusion, scene understanding, object recognition, and data restoration. Despite its successful applications in a set of computer graphics, vision and medical image analysis tasks, 3D matching computation remains challenging when the corresponding regions/patterns of the matching data lack saliency (due to small feature size or ambiguous characteristics) or exhibit significant topological/geometric inconsistency (due to data damage, occlusion, or noise). Our research goal is to explore novel matching strategies that can tackle the above difficulties and develop reliable algorithms for practical data reconstruction and restoration applications. Data restoration of fragmented or damaged geometric or image data is to reconstruct their original complete shapes or figures. Its direct applications includes forensic evidence restoration and archaeological heritage preservation. In this dissertation, we systematically develop a set of matching algorithms, involving different geometric primitives (from curve to surface) and different number of matching objects (from pairwise matching to multi-object matching). We demonstrate these techniques’ applications in a forensic data restoration pipeline of fragmented skull reassembly, skull damage repair, ancestry assessment/prediction, and facial reconstruction. This restoration pipeline is promising in migrating