The application discloses a
chin-up object borrowing detection method based on
visual detection. The method continuously acquires
human body key point coordinates including shoulder,
elbow, hand,
crotch, knee, foot and the like through a camera. The
system firstly confirms that a person enters a preparation state through calculation of a hand-raising judgment
score, then calculates an upper bar
score based on the longitudinal distance between the hands and the
horizontal bar line in the test stage, calculates a falling bar
score based on the longitudinal distance between the feet and the ground straight line, and determines a detection frame interval. The method calculates a single-foot suspension continuous score in the interval, identifies a suspension interval, calculates a person rising score for each suspension interval, judges whether there is a rising behavior by analyzing the longitudinal
coordinate change of the shoulder and the
crotch, and determines that there is a rule violation behavior of stepping on an object to borrow the upper bar in the
chin-up process when it is detected that there is a rising behavior in at least one suspension interval. The method can automatically and accurately detect the rule violation behavior in the
chin-up test, and improves the fairness and accuracy of the test.