{'fraction_non_alphanumeric': 0.013799448022079117, 'fraction_numerical': 0.0, 'mean_word_length': 4.881081081081081, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Development of a Moving Shadow Detection Method for Indoor Scene Activity Tracking

We present a simple computational model that works in the RGB colour space to detect moving shadow pixels from video sequences of indoor scenes, illuminated in each case by a fixed yelloworange source of light. A channel ratio test for shadows cast on non-coloured natural wooden surfaces is proposed that can be appended to the developed scheme so as to reduce the otherwise high false detection rate. The core method, based on a Lambertian hypothesis, has been adapted to work well for near-matte surfaces by suppressing highlights. The results reported, based on an extensive data analysis conducted on some of the crucial parameters involved in the model, not only bring out the subtle details of the parameters, but also remove the ad hoc nature of the chosen thresholds to a certain extent. The method has been tested on various indoor video sequences; the results obtained indicate that it can be satisfactorily used to mark or eliminate the strong portion of the foreground-moving shadow region.