Method for counting pedestrian flow from multiple views under complex scene of traffic junction
A technology for complex scenes and traffic intersections. It is applied to the counting, calculation, and counting objects of randomly distributed items. It can solve problems such as inability to adapt to people flow statistics, inability to adjust camera angles, and inability to utilize existing equipment.
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Embodiment 1
[0049] Embodiment one: see figure 2 , the present invention is applicable to the multi-view method of counting the flow of people in the complex scene of the traffic intersection, and its implementation steps are as follows:
[0050] First, use the hybrid codebook algorithm to model the background of the video, detect and segment moving objects;
[0051] Then, use the optical flow method to calculate the motion vector, get the speed and direction of the moving target, distinguish the vehicle and pedestrian according to the speed and direction of the moving target, remove the vehicle target, extract the pedestrian target and calculate the pedestrian direction;
[0052] Finally, a virtual door is set, and the number of pedestrian targets passing through the virtual door is counted according to the pedestrian direction and the pre-calibrated virtual door round-trip direction.
Embodiment 2
[0053] Embodiment two: see figure 2, image 3 , Figure 4 , this embodiment is applicable to the multi-view people flow statistics method in the complex scene of the traffic intersection, and the hybrid codebook model is used to realize the detection of the moving object.
[0054] Detection of moving objects is a fundamental task in many computer vision and video analysis applications. Currently commonly used and effective foreground detection methods include mixed Gaussian models, codebooks, and non-parametric background models.
[0055] The mixed Gaussian model uses the video frame to compare with the established mixed Gaussian background model, and estimates the moving target through the change of the reference quantity. This method can handle complex and slowly changing backgrounds, but when the environment changes drastically, the background model It will also fail, and due to the calculation of the probability distribution of each pixel, the computational complexity ...
Embodiment 3
[0077] Embodiment three: see figure 2 , image 3 , Figure 4 , Figure 5 , Image 6 , this embodiment is applicable to the multi-view pedestrian flow statistics method in the complex traffic intersection scene, using the optical flow method to calculate the speed and direction of the moving object, and distinguishing vehicles and pedestrians according to the speed and direction of the moving object.
[0078] The traffic intersection scene is complex, and there are a large number of mixed traffic of people and vehicles. If the vehicles passing through the intersection cannot be well filtered out, the statistical results will be greatly affected. At present, many people counting products adopt the method of recognition and classification. First, the characteristics of people or vehicles are extracted, and then the classifier is trained for training and classification, so as to achieve the purpose of separating people and vehicles. However, under the conditions of complex sc...
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