{'fraction_non_alphanumeric': 0.018484288354898338, 'fraction_numerical': 0.0, 'mean_word_length': 5.524096385542169, '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}}
Occlusion-Resistant Camera Design for Acquisition of Active Environments

Abstract We propose a family of Occlusion-Resistant Camera (ORC) designs for acquiring active environments despite the presence of moving interfering occluders. Being able to capture images in an in-use environment increases acquisition efficiency and quality without having to close-off the targeted site. Our cameras explicitly remove interfering dynamic occluders from acquired data in real-time and during live capture. Our key idea is to capture the scene at least twice from each viewpoint as the camera moves continually to sweep the scene and sample all surfaces. Our approach creates a single portable device combining the benefits of a stationary camera, which detects moving interfering occluders by image differencing, with those of a dynamic camera, which achieves scene coverage for inside-looking-out modeling. We describe our family of designs that progressively trades complexity for stricter camera orientation constraints, analyze their performance, and present a first ORC implementation.