CPC G06V 40/23 (2022.01) [A61B 5/1116 (2013.01); A61B 5/1118 (2013.01); A61B 5/1128 (2013.01); A61B 5/725 (2013.01); A61B 5/7405 (2013.01); A63B 24/0062 (2013.01); G06T 7/248 (2017.01); G06T 7/74 (2017.01); A63B 2024/0068 (2013.01); A63B 2220/806 (2013.01); A63B 2230/62 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30196 (2013.01)] | 20 Claims |
1. A method for monitoring a person performing a physical exercise based on a sequence of image frames showing an exercise activity of the person, the method comprising:
extracting, based on the sequence of image frames, for each image frame a set of body key points using a neural network, the set of body key points being indicative of the person's posture in the image frame;
deriving, based on a subset of the body key points in each image frame, at least one characteristic parameter indicating the progression of a movement of the person, wherein at least one of the characteristic parameters is derived from the subset of body key points in the sequence of image frames using machine learning and wherein the at least one characteristic parameter is not equal to any coordinate value of a body key point; and
detecting a start loop condition by evaluating a time progression of at least one of the characteristic parameters, said start loop condition indicating a transition from a start posture of the person to a movement of the person when performing the physical exercise.
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