30 results about "Targeted surveillance" patented technology

Systems and methods for cloud-based surveillance for a target surveillance area are disclosed. At least two input capture devices and at least one user device are communicatively connected to a cloud-based analytics platform. At least one input capture device is a mobile device with visual sensors. The cloud-based analytics platform automatically analyzes received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area.

Systems and methods for cloud-based surveillance for a target surveillance area are disclosed. At least two mobile input capture devices (ICDs) are communicatively connected to a cloud-based analytics platform via a data communication device. At least one user device can access to the cloud-based analytics platform. The cloud-based analytics platform automatically analyzes received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area. In one embodiment, the at least two mobile ICDs are Unmanned Aerial Vehicles (UAVs).

Systems and methods for cloud-computing network with distributed input devices and a cloud-based analytics platform for automatically analyzing received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area.

Systems and methods for cloud-computing network with distributed input devices and a cloud-based analytics platform for automatically analyzing received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area.

Systems and methods for cloud-computing network with distributed input devices and a cloud-based analytics platform for automatically analyzing received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area.

Systems and methods for cloud-computing network with distributed input devices and a cloud-based analytics platform for automatically analyzing received 2-Dimensional (2D) video and / or image inputs for generating 3-Dimensional (3D) surveillance data and providing 3D display for a target surveillance area.

The invention provides a clutter suppression method suitable for slow target surveillance radar, which includes the following steps: (S1) setting a low-order FIR high-pass filter to carry out high-pass filtering on a slow target; (S2) setting an MTD filter bank to carry out speed filtering on the slow target after high-pass filtering to obtain filtered data; (S3) carrying out filtering rearrangement on the filtered data; and (S4) carrying out Doppler sidelobe cancellation processing on the data after filtering rearrangement, so as to achieve clutter suppression. Through the design, the problems of false alarm and background elevation of a non-zero filter caused by clutter are solved without additional processing resources, the improvement factor and the system signal-to-clutter ratio are improved, and the detection performance of ground surveillance radar for slow and weak targets is satisfied. The method of the invention has the advantages of flexibility, high accuracy, small amount of calculation and good versatility, and is suitable for popularization and application.

The invention belongs to the field of multi-UAV regional monitoring route planning, and discloses a DQN-based route planning method for multi-UAV regional monitoring, including: setting the target monitoring region of the UAV group, including N UAVs, Set an airborne radar on each drone, and each drone flies at a constant speed; model the route planning of the drone group; determine the state and action of the drone; establish a deep neural network; get the target value of the neural network ; Plan the route of N drones, get a limited number of training samples during the flight of the drone group, and train the deep neural network through the samples. The trained neural network can predict the samples that have not been seen. When the current state of the UAV swarm is input, the neural network can be used to know which action to take to fly, and the monitoring coverage of the next step will be the largest. The route planned in this way can enable the UAV group to effectively cover the surveillance area in real time.

The embodiment of the present invention discloses a method and device for resuming video surveillance video, which is applied to a client. The method includes: obtaining a download instruction; judging whether there is a breakpoint corresponding to the start time and end time carried by the download instruction Identification; if so, according to the start time, find the currently downloaded part of the surveillance video corresponding to the target surveillance video; determine the download breakpoint time of the target surveillance video according to the part of the surveillance video; send the download breakpoint time and end time to the storage target The target monitoring device of the monitoring video, so that the target monitoring device sends the video code stream from the download breakpoint to the end time of the target monitoring video to the client; receives and saves the video code stream. By adopting this solution, when the download of the target surveillance video is interrupted and downloaded again, the download can be resumed from the download breakpoint, and there is no need to re-download from the start of the target surveillance video, which can save a lot of download time and traffic.

The invention discloses a control method, device, equipment and storage medium of a video monitoring cluster. The control method of the video monitoring cluster includes: determining the location information of a monitoring location; determining a target monitoring device from the video monitoring cluster according to the location information , wherein, the video monitoring cluster includes at least two monitoring devices; determining the control parameters of the target monitoring device based on the azimuth relationship between the target monitoring device and the monitoring site; controlling the target according to the control parameters A monitoring device, for collecting video information of the monitoring location through the target monitoring device. According to the technical solution of the embodiment of the present invention, the target monitoring equipment and its control parameters are determined through the positional relationship between the monitoring location and each monitoring equipment of the video monitoring cluster, and the remote and automatic regulation of the target monitoring equipment is realized to collect the video information of the monitoring location and control the efficiency. High, saving labor and time costs.

The present invention relates to a security alarm method and a chip. The method includes: obtaining at least one group of monitoring videos of a target area; determining the spatial position information of equipment corresponding to at least one group of monitoring videos, so as to obtain the logic between each group of monitoring videos relationship; according to the logical relationship, construct the video map corresponding to the target area; use the pre-trained detection model to judge whether there is an alarm event in at least one group of surveillance videos; when the judgment result is yes, determine the target surveillance video with the alarm event, and Generate an alarm signal; determine the relevant monitoring video that has a logical relationship with the target monitoring video according to the video map; send the alarm signal, target monitoring video and related monitoring video to the monitoring client, so as to respond to the alarm event according to the target monitoring video and related monitoring video to process. This solution can improve the processing efficiency of alarm events.

The present invention provides a monitoring video processing method and device, which are applied to a bastion host communicating with a video management server and a user terminal. The method includes: receiving a surveillance video acquisition request sent by a user terminal, and obtaining a target surveillance video corresponding to the request from a video management server according to the surveillance video acquisition request; finding whether there is a decoded surveillance video in the decoded surveillance video of the bastion machine. target surveillance video; when it exists, render the decoded target surveillance video and send it to the user terminal for display; when it does not exist, decode the target surveillance video to obtain the decoded target surveillance video video, and render the decoded target surveillance video and send it to the user terminal for display. The method can solve the problem of high performance consumption of the bastion host when different user terminals view the same surveillance video, and improve the service life of the bastion host.

The invention discloses a crowd event identification method, device, electronic equipment and system, belonging to the field of crowd event identification. The method includes: acquiring a monitoring video of a target area; acquiring at least one target monitoring image group from the monitoring video, each target monitoring image group including a plurality of continuous monitoring video frames; Crowd event identification is carried out in the monitoring image group, and the crowd event model is obtained through training of multiple crowd event image groups, each crowd event image group includes multiple crowd event images reflecting the process of crowd event occurrence; according to the recognition results, it is determined whether there is a crowd event in the target area . The invention can improve the accuracy of identifying crowd events.

The double-camera linkage structure-based close-up tracking and monitoring method for video moving targets disclosed by the present invention uses a panoramic monitoring camera to identify targets in the monitoring area, determine the position, running speed and direction of the target, and after locking and tracking the target, the target information is Pass it to the close-up tracking camera that is controlled by the pan / tilt. The close-up tracking camera will close-up the locked target, zoom in and track it, and display the close-up picture of the target, so as to obtain more information about the target. It can not only monitor the panorama, but also automatically judge suspicious targets, and realize the function of close-up tracking.