Abnormal falls in public places have significant safety hazards and can easily lead to serious\nconsequences, such as trampling by people. Vision-driven fall event detection has the huge advantage\nof being non-invasive. However, in actual scenes, the fall behavior is rich in diversity, resulting in\nstrong instability in detection. Based on the study of the stability of human body dynamics, the\narticle proposes a new model of human posture representation of fall behavior, called the â??five-point\ninverted pendulum modelâ?, and uses an improved two-branch multi-stage convolutional neural\nnetwork (M-CNN) to extract and construct the inverted pendulum structure of human posture in\nreal-world complex scenes..............................
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