Method and system for determining that road pedestrians have attraction relationship
A pedestrian and suction technology, applied in the direction of road vehicle traffic control system, collision avoidance system, traffic control system, etc., can solve the problem of pedestrians becoming dangerous pedestrians.
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Embodiment 1
[0081] Repulsion pedestrian classification situation
[0082] This example is aimed at the classification of repulsive pedestrians, and the simulation results are as follows figure 2 Shown. figure 2 Lists the three images in the continuous video frame and the pedestrian classification result of this frame. Among them, the magnetic probability of pedestrians only meets the requirement of magnetic pedestrians. In the video, three pedestrian targets move at a speed of about 1.2m / s, of which two pedestrians move in a positive direction and one pedestrian moves in a negative direction, and they all keep moving in a straight line without changing the moving speed. From frame 8 to frame 33, pedestrians B and C keep approaching. Until the 33rd frame, the repulsion probability of pedestrians B and C exceeds δ, and they are judged as repulsive pedestrians. Similarly, at the 72nd frame, when the repulsion probability of pedestrians A and C exceeds δ, they are judged to be repulsive pedes...
Embodiment 2
[0084] Classification of suction pedestrians
[0085] This example is aimed at the classification of repulsive pedestrians, and the simulation results are as follows image 3 Shown. image 3 The three images in the continuous video frame and the pedestrian classification result of this frame are listed. Among them, the magnetic probability of pedestrians only meets the requirements of magnetic pedestrians. In the video, the three pedestrian targets move in the positive direction at a speed of about 1.2m / s, and all keep moving in a straight line without changing the moving speed. From frame 11 to frame 39, pedestrians B and C keep walking together. Until the 39th frame, the suction probability of pedestrians B and C exceeds δ, and they are judged as suction pedestrians. At the next 75th frame, pedestrians B and C maintain the judgment result of the suction pedestrian.
Embodiment 3
[0087] Classification of non-magnetic pedestrians
[0088] This example is aimed at the classification of non-magnetic pedestrians. The simulation results are as follows Figure 4 Shown. Figure 4 The three images in the continuous video frame and the pedestrian classification results of this frame are listed. Among them, the magnetic probability of the pedestrian only has the probability of no magnetic force to meet the determination requirements of the magnetic pedestrian. In the video, the three pedestrian targets move in the negative direction at different speeds, and all keep moving in a straight line without changing the moving speed. The speed of pedestrian A is about 0.5m / s, and the speed of pedestrians B and C is about 1.3m / s. . In the ninth frame, the non-magnetic probability of pedestrian A is calculated to be 1, and it is determined as a non-magnetic pedestrian. In the subsequent 42nd and 103rd frames, pedestrian A maintains the determination result of non-magnetic pe...
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