{'fraction_non_alphanumeric': 0.018439716312056736, 'fraction_numerical': 0.0, 'mean_word_length': 5.247787610619469, '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}}
Enhanced Kernel-Based Tracking for Monochromatic and Thermographic Video

In this paper, we present an enhanced kernel-based tracker for monochromatic and thermographic video. The technique presented here employs the image intensity and the Local Binary Pattern (LBP) to construct a two dimensional histogram representative of the grayscale values and the texture of the target under study. With the histogram at hand, we proceed to compute its power density function. The new location of the object is then determined making use of a mean-shift optimisation approach. We illustrate the performance of our method in both, thermographic and monochromatic footages and compare our results to an alternative.