The invention provides a marathon cross-country event tumble detection method based on an unmanned aerial vehicle and attitude
estimation, relates to the technical field of image recognition, constructs a P2 high-resolution detection
branch, retains the highest-frequency spatial texture details in a
human body image, and solves the problem of missing detection caused by feature
aliasing of minimum targets such as wrists and ankles. According to the method, a C2PSA module is embedded in the deep layer of a
backbone network, attention weights are concentrated in a
human body target area, a distributed sensing coordinate classification architecture is introduced to process X-axis and Y-axis feature vectors, and the defect that correlation between coordinate axes is ignored in an existing method is overcome. According to the method, a parallel Aux Head auxiliary
branch and a KLD
loss function are introduced, so that the model can tolerate labeling errors in the optimization process. According to the method,
false alarm filtering is carried out in combination with head motion logic, active stretching / shoelace tying and accidental falling are effectively distinguished, and the
false alarm rate in practical application is greatly reduced.