A detection method, device, equipment and medium for a traffic accident
A traffic accident and detection method technology, applied in the field of image processing, can solve problems such as low degree of intelligence, and achieve the effects of improving user experience, improving image processing efficiency, and shortening image processing time
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Embodiment 1
[0085] figure 1 It is a schematic flow chart of a traffic accident detection method disclosed in Embodiment 1 of the present application. The embodiment of the present application can be applied to the scene of fast and timely detection of traffic accidents. The method can be executed by a traffic accident detection device, which can be implemented by software and / or hardware implementation, which can be integrated inside the electronic device. The method specifically includes the following steps:
[0086] S101. Extract at least one frame of static image from a surveillance video stream.
[0087] S102. Identify set features of a traffic accident scene from at least one frame of the static image.
[0088] Wherein, the monitoring video can be obtained by shooting with multiple devices such as a fixed-point camera, a vehicle-mounted camera, or a drone, which is not specifically limited in this embodiment. That is to say, the monitoring video obtained by shooting with multiple...
Embodiment 2
[0112] Figure 4 It is a schematic flow chart of a traffic accident detection method disclosed in Embodiment 2 of the present application. On the basis of Embodiment 1, this embodiment will further "identify the set traffic accident scene features from at least one frame of static image" Optimized to "if the static image is multiple frames, then identify the set traffic accident scene features from the multiple frames of the static image", the method specifically includes the following steps:
[0113] S401. Extract at least one frame of static image from a surveillance video stream.
[0114] S402. If the static image includes multiple frames, identify a static target and / or a dynamic target from the multiple frames of the static image as a target object.
[0115] It can be understood that, in this embodiment, the static target and / or the dynamic target refer to the static target; or refer to the dynamic target; or may also refer to the static target and the dynamic target.
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Embodiment 3
[0160] Figure 6 It is a schematic flow chart of a traffic accident detection method disclosed in Embodiment 3 of the present application. On the basis of Embodiment 1 above, this embodiment further optimizes "determining the traffic accident detection result according to the identified characteristics of the traffic accident scene" as follows: "According to the identified characteristics of the traffic accident scene, if it is determined based on the set alarm rules that the alarm threshold is reached, an alarm notification is triggered", the method specifically includes the following steps:
[0161] S601. Extract at least one frame of static image from a surveillance video stream.
[0162] S602. Identify set traffic accident scene features from at least one frame of the static image.
[0163] S603. According to the identified characteristics of the traffic accident scene, if it is determined based on the set alarm rule that the alarm threshold is reached, an alarm notificat...
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