{'fraction_non_alphanumeric': 0.016467065868263474, 'fraction_numerical': 0.0, 'mean_word_length': 5.4326923076923075, '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}}
Pedestrian-Flow Statistics Algorithm Based on Image Processing

The automatic statistics to pedestrian flow can greatly improve the duty staff efficiency and thus becomes the hot research field. This paper presents a pedestrian flow statistics algorithm based on image-processing. Our research is on the basis of color histogram and mean-shift algorithm, and introduces the SVM model through generating confidence function to judge the actual attribute of background pixels. Such way improves the accuracy of target detection. Experimental results prove our algorithm better handles to pedestrian's coverage problem and meets the requirement of real-time and accuracy.