CN101106700A - Intelligent target detail capturing device and method in video monitoring system - Google Patents
Intelligent target detail capturing device and method in video monitoring system Download PDFInfo
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Abstract
The invention relates to an intelligent target details acquisition device of video monitoring systems and the method thereof. The device uses one or a plurality of fixed cameras to monitor the whole monitored area, and uses one movable camera to capture target details in the set region. First of all, the invention obtains moving targets in the region from the images captured by the fixed cameras through a processing module; then tracks the separated moving targets and determines the motion state; if any target enters the set region, then according to the preset position parameters and focal length parameters of the region, the invention will adjust the direction and the focal length of the movable camera to capture detailed images of the target in the region; at the same time, the invention can conduct storage and remote transmission of the images as required. The invention has the advantages that the invention provides the video monitoring device which not only can monitor a large area, but also can automatically capture details of physical targets, and the method thereof, solving the contradiction between the monitored scope and the monitored target details in the prior art.
Description
Technical Field
The invention belongs to the technical field of video monitoring, and relates to an intelligent target detail capturing device and method in a video monitoring system.
Background
Currently, in the technical field of video surveillance, most video surveillance videos can only record the motion state of a target in a surveillance scene, but cannot provide clear target detail information. Therefore, the use value of the video recording is greatly reduced. The methods for improving the definition of target details on the premise of eyes mainly include two types: one method is to use a high-quality imaging device to improve the imaging resolution, or to provide image information of target details by arranging a plurality of cameras in a scene, which has the disadvantage of increasing the cost of the video surveillance system; the other method is to adopt a video monitoring system with a pan-tilt camera, but the existing methods work in a manual adjustment mode, and have the defects that intellectualization cannot be realized, and the target detail image acquisition efficiency is low.
Therefore, the contradiction between the video monitoring range and the specific target detail acquisition in the existing monitoring system needs to be solved, and the video monitoring system which can effectively solve the contradiction between the video monitoring range and the specific target detail acquisition and does not increase the cost is provided.
Disclosure of Invention
The invention aims to provide an intelligent target detail capturing device and method in a video monitoring system, which can monitor and record a video on a large scene, and can intelligently and efficiently capture target detail information entering a set area, thereby solving the contradiction between large scene monitoring and target detail information capturing and improving the use value of the monitoring video.
In order to achieve the purpose, the technical scheme of the invention is as follows:
the intelligent target detail capturing device in the video monitoring system is used for capturing a panoramic image of a monitored area and a target detail image of a set area, and consists of an imaging module 1, an input module 2, a processing module 3, a control module 4, a storage module 5 and a transmission module 6; the imaging module 1 is used for imaging the panorama and the target details and outputting video images of the imaged panorama and the target details; the input module 2 is connected between the imaging module 1 and the processing module 3 and is used for capturing a video image output by the imaging module 1; the processing module 3 is connected between the input module 2 and the control module 4, and is used for processing the panoramic video image captured by the input module 2 and detecting whether a target appears in a set area; the control module 4 is connected between the processing module 3 and the imaging module 1 and is used for controlling the imaging module 1 to capture an image of the target details; the storage module 5 and the transmission module 6 are respectively connected to the input module 2, the storage module 5 is used for storing all captured video images, and the transmission module 6 is used for transmitting the video images to a remote terminal.
The imaging module 1 is composed of one or more fixed cameras 7 and a holder camera 8, the fixed cameras 7 are connected with the input module 2 and used for panoramic imaging, and the holder camera 8 is connected with the input module 2 and the control module 4 and used for target detail imaging.
An intelligent target detail capturing method in a video monitoring system comprises the following steps: the fixed camera 7 images the panorama of the monitoring area; the input module 2 captures a panoramic video image of a monitored area and outputs the image to the processing module 3; the processing module 3 establishes a background model by using a sliding average method, performs area numbering on a set area in the monitoring area, and records the position parameter and the focal length parameter of the corresponding numbered area captured by the cloud platform camera 8; the processing module 3 extracts the moving target by using a background removal method; the processing module 3 tracks and detects the moving target and judges whether the moving target enters a set area; if the moving target does not enter the set area, continuing to track the moving target; if the moving target enters a set area, outputting the number and the control parameters of the set area to the control module 4; the control module 4 controls the pan-tilt camera 8 to rotate to the position corresponding to the area, which is recorded in advance by the processing module 3, according to the received serial number and the control parameter of the set area, and controls the pan-tilt camera to adjust the focusing parameter of the pan-tilt camera; the pan-tilt camera 8 captures an image of the target details; the storage module 5 and the transmission module 6 store and transmit the captured image.
After the step of capturing the panoramic video image of the monitored area by the input module 2 and outputting the image to the processing module 3, the method further comprises the step of storing and transmitting the captured image by the storage module 5 and the transmission module 6.
The invention has the beneficial effects that: the fixed camera is used for capturing the panoramic video image of the monitored area, the control module is used for controlling the pan-tilt camera to intelligently and efficiently capture the target detail video image of the set area, the contradiction between panoramic monitoring of the monitored area and target detail capturing of the set area is solved, and the use value of the monitoring video is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent target detail capturing device in a video surveillance system according to the present invention.
In the figure: 1. imaging module, 2, input module, 3, processing module, 4, control module, 5, storage module, 6, transmission module, 7, fixed camera, 8, cloud platform camera.
Detailed Description
The invention is described in further detail below with reference to the attached drawing figures:
as shown in fig. 1, the intelligent target detail capturing apparatus in the video monitoring system of the present invention is composed of an imaging module 1, an input module 2, a processing module 3, a control module 4, a storage module 5 and a transmission module 6, wherein the imaging module 1 is composed of one or more fixed cameras 7 and a pan-tilt camera 8. One or more fixed cameras 7 are used for imaging panorama, a pan-tilt camera 8 is used for imaging target details, an input module 2 is used for capturing input video images, a processing module 3 is used for processing images obtained by the fixed cameras, whether targets appear in set areas or not is detected, the pan-tilt camera 8 is controlled by a control module 4 to capture the target detail images, and a storage module 5 and a transmission module 6 are used for controlling the storage and the transmission of all collected images.
The intelligent target detail capturing method in the video monitoring system is realized as follows:
1. the imaging module 1 is responsible for the formation of image of panorama by one or more fixed cameras 7, and the camera direction, the focus of cloud platform camera 8 can be adjusted, and it is responsible for the formation of image of target detail.
2. The input module 2 is composed of a video capture card and a capture program and is responsible for image input and image format conversion. Setting contents such as resolution, image format, sampling interval and the like of the collected image by calling an initialization function of a driving program; and calling an acquisition function to finish the acquisition of all the images.
3. The processing module 3 implements the following functions:
1. the set area in each camera acquisition scene is set through a mouse, the serial number of the area is carried out, and meanwhile, the position parameter and the focal length parameter of the corresponding area captured by the holder camera 8 are recorded.
And establishing a background model by a moving average method, and updating background change caused by scene content change or illumination condition change.
And obtaining a motion area in each camera acquisition image by using a method of subtracting the background model from the current frame.
The treatment method comprises the following steps:
the method comprises the following processing steps of extracting a moving target by a background removal method:
1) Extraction of motion areas: extracting motion regions using background subtraction:
wherein, V (x, y, T) is a change region binary image, I (x, y, T) is an input image at time T, μ (x, y, T) is a background model at time T, and T is a threshold.
2) Background model update algorithm: and updating the background by adopting an improved moving average method, wherein the processing method comprises the following steps:
μ t ＝Mμ t-1 +(1-M)(αI t +(1-α)μ t-1 )
wherein M is a motion region template, mu t And mu t-1 And alpha is the update rate, wherein the background models are the background models at the time t and the time t-1.
And detecting and tracking the moving target, and outputting the number of the area to the control module when the target appears in the set area.
Video tracking processing, namely tracking a moving target and judging a moving state, wherein the processing steps are as follows:
a) And (3) calculating a characteristic value, namely calculating the characteristic value of the moving target extracted after the operation of step 1), including a mass center and a tracking window.
The centroid and the tracking window size are selected as eigenvalues to track the target.
Firstly, a tracking window of a moving target is set, namely, a circumscribed rectangle of the target is used as the tracking window.
L＝x max -x min
W＝y max -y min
Wherein x is max ，x min Respectively, the maximum and minimum coordinates, y, of the target in the horizontal direction max ，y min The maximum coordinate and the minimum coordinate of the target vertical direction are respectively.
After each tracking window is marked, the centroid of the target in the window is determined, and the input image is set as f (x, y), as shown in the following formula:
f (x, y) is the moving object image in the tracking window, the centroid of the window can be calculated, and the centroid coordinate of the window is set as
b) And establishing a motion model of the system by using a Kalman filter, and defining a state vector to predict the position where the moving target can appear in the next frame.
The processing step adopts Kalman filtering to establish a motion estimation model for the system. The Kalman filtering is utilized to carry out motion estimation, noise interference can be reduced, the search range of feature extraction is narrowed, only the current tracking window needs to be detected, and the calculated amount is reduced.
Let the state vector s at time k +1 in the model k+1 From the vector s at time k k The transfer function and the noise component of (c). And the vector s at the moment when the vector is observed to be k +1 k+1 And noise decision.
The equation of state is as follows
s k+1 ＝As k +w k
Equation of measurement
z k+1 ＝Cs k+1 +v k+1
In the formula, w k 、v k+1 Normal white noise with a mean value of zero.
s k It is the state vector that is made up of one eight-dimensional vector:
in the formula, x k ，y k Respectively are the coordinates of the center of mass of the target,
unit displacement of the centroid coordinate in x, y directions, respectively, L xk ，L yk The width of the tracking window in the x, y directions,
respectively width of tracking windowUnit displacement in the x, y direction.
z k+1 Is an observation vector, and is composed of four-dimensional vectors.
Because the sampling interval is short, the moving speed of the moving object can be approximately considered to be constant, and the size of the tracking window does not change greatly, and the state transition matrix a is:
the observation matrix C is:
c) And (4) feature matching, defining a similarity function of the target, calculating a similarity function value by using the change of the target between frames and the feature value, and judging whether the target is the same tracking target.
First, define the centroid distance function of the ith object in the kth frame and the jth object in the (k + 1) th frame:
in the formula:
area difference function, i.e. comparing the window area of the ith object in the kth frame with the window area of the jth object in the (k + 1) th frame:
in the formula:
defining a similarity function
Δ(i，j)＝γD(i，j)+ξA(i，j)
In the formula, gamma and xi are weight values, and meet the condition that gamma is more than xi, gamma + xi =1, and delta (i, j) is less than or equal to 1.
If D (i, j) is smaller, the object is closer, and A (i, j) is smaller, the object shape is closer, and Δ (i, j) is smaller, the probability that the two objects are similar is maximum. Setting threshold T of similarity function Δ As a basis for not being the same object.
d) And updating the model, namely updating the motion model as the input of Kalman filtering of the next motion model.
When the minimum value of the similarity function is found, the subsequent targets of the same target are found, that is, the jth target of the (k + 1) th frame can be regarded as the ith target of the kth frame, that is, the two targets are the same target. At this time, the characteristic value of the jth target of the (k + 1) th frame is used as the input of the motion model estimation of the next frame, and so on, and the tracking of the model is completed.
2) And when the moving target is detected to enter the set area, outputting the number and the control parameters of the set area.
4. The processing steps of the control module 4 are as follows:
and searching corresponding position parameters and focal length parameters according to the area numbers generated by the image processing module, and outputting the position parameters and the focal length parameters to a control module of the holder camera through a control port.
The processing steps are as follows:
1. and searching corresponding position parameters and focal length parameters according to the area numbers generated by the image processing module, and outputting the position parameters and the focal length parameters to a control module of the holder camera through a control port.
2. And outputting a control command through a communication port, such as RS-232 or USB, and controlling the pan-tilt camera to rotate to a set position and adjusting the focusing parameters of the camera.
5. The storage module 5 compresses the images collected by each fixed camera 7 and the pan-tilt camera 8 and stores the compressed images in a hard disk, and the collected images can be compressed and stored by adopting formats such as MPEG-1, MPEG-4, WAVELET, H.263 and the like
6. The transmission module 6 can transmit the images collected by the cameras to a remote terminal through the network by adopting the Ethernet according to actual needs.
Claims (4)
1. An intelligent target detail capturing device in a video monitoring system is used for capturing a panoramic image of a monitored area and a target detail image of a set area, and is characterized by comprising an imaging module (1), an input module (2), a processing module (3), a control module (4), a storage module (5) and a transmission module (6); the imaging module (1) is used for imaging the panorama and the target details and outputting video images of the imaged panorama and the target details; the input module (2) is connected between the imaging module (1) and the processing module (3) and is used for capturing a video image output by the imaging module (1); the processing module (3) is connected between the input module (2) and the control module (4) and is used for processing the panoramic video image captured by the input module (2) and detecting whether a target appears in a set area; the control module (4) is connected between the processing module (3) and the imaging module (1) and is used for controlling the imaging module (1) to capture an image of the target details; the storage module (5) and the transmission module (6) are respectively connected to the input module (2), the storage module (5) is used for storing all captured video images, and the transmission module (6) is used for transmitting the video images to a remote terminal.
2. The intelligent target detail capturing device in the video monitoring system according to claim 1, wherein the imaging module (1) is composed of one or more fixed cameras (7) and a pan-tilt camera (8), the fixed cameras (7) are connected with the input module (2) for panoramic imaging, and the pan-tilt camera (8) is connected with the input module (2) and the control module (4) for target detail imaging.
3. An intelligent target detail capturing method in a video monitoring system is characterized by comprising the following steps:
a fixed camera (7) images the panorama of the monitored area;
the input module (2) captures a panoramic video image of a monitored area and outputs the image to the processing module (3);
the processing module (3) establishes a background model by using a moving average method, performs area numbering on a set area in a monitoring area, and records a position parameter and a focal length parameter of a corresponding numbered area captured by a holder camera (8);
the processing module (3) extracts a moving target by using a background removal method;
the processing module (3) tracks and detects the moving target and judges whether the moving target enters a set area or not;
if the moving target does not enter the set area, continuing to track the moving target;
if the moving target enters a set area, outputting the number and the control parameters of the set area to a control module (4);
the control module (4) controls the holder camera (8) to rotate to the position, corresponding to the area, recorded in advance by the processing module (3) according to the received serial number and the control parameter of the set area, and controls the holder camera to adjust the focusing parameter of the holder camera;
a pan-tilt camera (8) captures an image of the target details;
the storage module (5) and the transmission module (6) store and transmit the captured images.
4. An intelligent target detail capturing method in a video surveillance system according to claim 3, characterized in that after the step of capturing panoramic video images of the monitored area by the input module (2) and outputting the images to the processing module (3), the method further comprises the step of storing and transmitting the captured images by the storage module (5) and the transmission module (6).
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