{'fraction_non_alphanumeric': 0.027868852459016394, 'fraction_numerical': 0.0, 'mean_word_length': 5.0495049504950495, '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}}
Spatio-temporal consistent depth maps from multi-view video

The demand for high quality depth maps from stereo and multi-camera videos increases constantly. The main application for these depth maps is rendering new perspectives of the captured scene by means of Depth Image Based Rendering (DIBR). Accurate depth maps are the linchpin of DIBR. On the basis of a four-camera set-up, we show that combining hybrid recursive matching with motion estimation, cross -bilateral post-processing and mutual depth map fusion produces spatio-temporal consistent depth maps appropriate for artifact-free view synthesis.