{'fraction_non_alphanumeric': 0.022066198595787363, 'fraction_numerical': 0.0, 'mean_word_length': 5.198757763975156, '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}}
The method for defocusing selfie taken by mobile frontal camera using burst shot

In this paper, we present a novel human segmentation technique that automatically detects upper-body region in the selfie. To detect and segment upper-body without user interactions, we develop an initial tri-map by combining face detection results and upper-body shape prior in the selfie. Moreover, we employ motion vectors between two images captured in a short time interval to deal with various human poses and cluttered backgrounds. From motion vectors, we estimate the implicit depth layers without auxiliary hardware or time-consuming algorithms. By integrating information from the face detector, shape prior, and motion vectors, we detect and segment the human upper-body accurately. We also implement the proposed algorithm on the mobile phone. In the extensive experiments on selfie dataset, the proposed method shows competitive results in terms of accuracy/recall and outperforms the previous methods.