{'fraction_non_alphanumeric': 0.02694610778443114, 'fraction_numerical': 0.00499001996007984, 'mean_word_length': 4.8313953488372094, '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}}
Efficient Indexing and Storage Algorithm for Visual Databases

A novel approach pertaining to the fast and efficient retrieval and storage of video sequences utilizing MPEG-1/2 motion vectors is presented in this paper. A clip first must be segmented into consistent video segments based on the basic editing effects - cuts, dissolves, and wipes. All group of pictures (GOPs) are then extracted from the clip and decomposed further into I-frames and P-frames (B-frames are disregarded). The initial frame of the sequence is manually segmented into objects, and the selected objects are automatically tracked through the entire sequence using MPEG-1/2 motion vectors. Features pertaining to the edge histogram are extracted from each tracked object (I/P frames only) and then maintained with the associated frame. An example image or video clip is then presented to the system and the 5 best matching images are retrieved. Results are shown for the standard video sequences such as foreman, tennis, etc.