Postures anomaly tracking and prediction learning model over crowd data analytics

ABSTRACT: Innovative technology and improvements in intelligent machinery, transportation facilities, emergency systems, and educational services define the modern era. It is difficult to comprehend the scenario, do crowd analysis, and observe persons. For e-learning-based multiobject tracking and predication framework for crowd data via multilayer perceptron, this article recommends an organized method that takes e-learning crowd-based type data as input, based on usual and abnormal actions and activities. After that, super pixel and fuzzy c mean, for features extraction, we used fused dense optical flow and gradient patches, and for multiobject tracking, we applied a compressive tracking algorithm and Taylor series predictive tracking approach. The next step is to find the mean, variance, speed, a

SUBMITTER: Aljuaid H 

PROVIDER: S-EPMC10280427 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature