CN102682284A - Early-warning scheduling framework based on cloud and robbing detection method in framework - Google Patents

Abstract

The invention discloses an early-warning scheduling framework based on a cloud and a robbing detection method in the framework. The method comprises the following steps of: obtaining a video monitoring image; then utilizing a background elimination method to divide a foreground and a background of the obtained video monitoring image; defining an area-of-interest interface of a background elimination image; comparing a pre-stored template region with an effective area-of-interest to obtain a comparison result of left and right arms; and finally, identifying the comparison result of the left and right arms to obtain an effective comparison result of the left and right arms. The system comprises a monitoring video shooting end, an early-warning scheduling system based on the cloud, a monitoring center end and a scheduling display end, wherein the early-warning scheduling system based on the cloud identifies based on the robbing detection method. According to the invention, the video monitoring image of robbing can be accurately identified, the processing efficiency of the robbing detection method is improved and a management resource is intensively optimized. The early-warning scheduling framework based on the cloud and the robbing detection method in the framework disclosed by the invention can be widely applied to the field of public security.

Description

A kind of early warning scheduling framework and robbery method for detecting wherein based on cloud

Technical field

The present invention relates to video image identification technology and cloud computing technology, relate in particular to a kind of early warning scheduling framework and robbery method for detecting wherein based on cloud.

Background technology

People's living standard improves gradually now, but gap between the rich and the poor but widens gradually, so the probability that robbery crime takes place has the phenomenon that obviously raises year by year.In order to prevent to hit robbery crime and to maintain public order, people have taked a lot of defence measures, for example video monitoring system, public security early warning, go out alarm system, sub-district defendance etc., and then strengthen security administration and safeguard social public security.Yet video monitoring system now can not be discerned plundering on-the-spot video pictures, and then monitors and the police strength allotment.

Summary of the invention

In order to solve the problems of the technologies described above, the purpose of this invention is to provide the high and fireballing robbery method for detecting of accuracy.

Another object of the present invention provides response and the fast a kind of early warning scheduling framework based on cloud of processing speed.

The technical scheme that the present invention adopts is: plunder method for detecting, the step of this method comprises:

S1, the video monitoring picture is obtained;

S2, employing background elimination method are carried out cutting apart of prospect and background to the video monitoring picture that obtains, and then are obtained the background elimination chart;

S3, the background elimination chart is carried out the area-of-interest boundary definition, and then obtain effective area-of-interest;

Comparing to effective area-of-interest in the template zone that S4, basis prestore, and then draws arm comparison result in the left and right sides in effective area-of-interest;

S5, left and right sides arm comparison result is verified, and then obtained effective left and right sides arm comparison result.

Further, said step S2 comprises:

S21, employing median method generate the reference background picture;

S22, the difference of getting current video monitored picture and reference background picture, and described difference taken absolute value;

S23, said absolute value is carried out binaryzation, and then obtain the background elimination chart of binaryzation according to threshold value;

S24, employing morphology carry out denoising to the background elimination chart of binaryzation.

Further, said step S3 comprises:

S31, employing pixel vertical projection and pixel level projection are carried out the area-of-interest boundary definition to the background elimination chart;

S32, the boundary definition scope of area-of-interest is outwards expanded, and then obtained effective area-of-interest according to the border preset value.

Further, adopt the pixel vertical projection background elimination chart is carried out area-of-interest left and right sides boundary definition and to adopt the pixel level projection that the background elimination chart is carried out the area-of-interest up-and-down boundary and define among the said step S31.

Further, said step S4 adopts scan mode according to the template zone that prestores effective area-of-interest to be compared one by one, and then draws arm comparison result in the left and right sides in effective area-of-interest.

Further, said step S5 comprises:

S51, calculate in effective area-of-interest the left arm degree of approximation measured value of left arm in the left arm comparison result and template zone, and calculate in effective area-of-interest the effectively right arm degree of approximation measured value of right arm comparison result and the regional right-of-center in political views's arm of template;

S52, left arm degree of approximation measured value and right arm degree of approximation measured value are carried out addition, and then obtain the left and right sides arm degree of approximation and measure additive value;

S53, according to degree of approximation measurement threshold, judge that whether the left and right sides arm degree of approximation measure additive value greater than degree of approximation measurement threshold, if, execution in step S54; Otherwise, then get rid of left and right sides arm comparison result;

S54, to carrying out left and right sides arm position judgment in the arm comparison result of the left and right sides, pre-conditioned if the horizontal range between the outside vertical of left and right sides arm distance and the left and right sides inboard arm all meets, then export effective left and right sides arm comparison result; Otherwise, then get rid of left and right sides arm comparison result.

Further, the computing formula of left arm degree of approximation measured value and calculating right arm degree of approximation measured value is following among the step S52:

$\left\{\begin{array}{c}{s}_1=w_F\·\mathrm{Area}(X_F\∩T_F)+w_B\·\mathrm{Area}(X_B\∩T_B)\\ s_2=w_F\·\mathrm{Area}(X_F\∩T_B)+w_B\·\mathrm{Area}(X_B\∩T_F)\\ \mathrm{SM}=s_1-s_2\end{array}\right.$

Wherein, W _FAnd W _BBe weighting coefficient, X _BRepresent the background pixel in effective area-of-interest, T _BBackground pixel in the representation template zone, when calculating left arm degree of approximation measured value, X _FRepresent the left arm foreground pixel in effective area-of-interest, T _FLeft arm foreground pixel in the representation template zone, SM are represented left arm degree of approximation measured value; When calculating right arm degree of approximation measured value, X _FRepresent the right arm foreground pixel in effective area-of-interest, T _FRight arm foreground pixel in the representation template zone, SM are represented right arm degree of approximation measured value.

What further, the horizontal range between the outside vertical of left and right sides arm distance and the left and right sides inboard arm met among the said step S54 is as follows pre-conditioned:

$\left\{\begin{array}{c}{d}_{\mathrm{Ver}}\≤K_1\·{\stackrel{\‾}{d}}_{\mathrm{Ver}}\\ K_2\·{\stackrel{\‾}{d}}_{\text{Hor}}\≤d_{\mathrm{Hor}}\≤K_3\·{\stackrel{\‾}{d}}_{\mathrm{Hor}}\end{array}\right.$

D wherein _VerThe outside vertical distance of expression left and right sides arm, d _HorHorizontal range between the inboard arm of the expression left and right sides,

The mean value or the reference value of the outside vertical distance of expression left and right sides arm,

The mean value or the reference value of the horizontal range between the inboard arm of the expression left and right sides, K ₁, K ₂, K ₃Be constant.

Another technical scheme that the present invention adopts is: a kind of early warning scheduling framework based on cloud comprises:

Monitor video shooting end is used to obtain the video monitoring picture, and the video monitoring picture is sent to early warning dispatching system and Surveillance center's end based on cloud;

Early warning dispatching patcher based on cloud; Be used for the geographical position that the video monitoring picture receives and shooting is held to monitor video is obtained; After adopting the robbery method for detecting that the video monitoring picture that receives is discerned; Hold to Surveillance center based on effective left and right sides arm comparison result that recognizes and then transmission information; And confirmation received the police strength resource table search that mate based on the geographical position of monitor video shooting end the back, and then obtain to send coupling police strength resource table to transferring display end behind the coupling police strength resource table, after being received, preferred police strength resource table sends to police station's end;

Surveillance center's end is used for information and video monitoring picture are received and send confirmation to the early warning dispatching system based on cloud;

Transfer display end, be used for coupling police strength resource table is received and shows, and send preferred police strength resource table to early warning dispatching system based on cloud.

Police station's end is used for preferred coupling police strength resource table is received.

Further, said early warning dispatching system based on cloud comprises:

Subsystem is plundered in cloud monitoring, is used for the video monitoring picture obtained and adopt plundering method for detecting the video monitoring picture being discerned, according to the effective left and right sides arm comparison result that recognizes and then send information and hold to Surveillance center;

Information scheduler subsystem; Be used for the geographical position that the video monitoring picture receives and shooting is held to monitor video is obtained; Send the load balancing of weighted information based on video monitoring picture and monitor video shooting end to cloud computing platform; And then the load balancing of cloud computing platform is that information processing is carried out with the server that empty limit optimization cooperates in cloud monitoring robbery subsystem searching geographical position; And confirmation received the back based on the geographical position distance the shortest coupling police station geographical position of the police station geographical position search that prestores from monitor video shooting end, will mate the police station geographical position and send to responding scheduler subsystem;

Responding scheduler subsystem; Be used for coupling police station geographic position is received; Real-time police strength resource table search and coupling police station geographic position corresponding coupling police strength resource table according to storage; And then obtain to send coupling police strength resource table to transferring display end behind the coupling police strength resource table, after being received, preferred police strength resource table sends to police station's end;

Said information scheduler subsystem discharges shared resource and shared resource given cloud computing platform when wait acknowledge information scheduling of resource process.

The invention has the beneficial effects as follows: through using this method, can discern the video monitoring picture of plundering exactly, thereby alleviate the personnel's of Surveillance center working pressure, significantly reduce the expense of human resources.

Another beneficial effect of the present invention is: through using this system; Can discern the video monitoring picture of plundering exactly; Thereby alleviate the personnel's of Surveillance center working pressure; And adopt the system architecture of cloud computing and on the system architecture of cloud computing, construct three sub-systems again, can improve the treatment effeciency and the concentrated optimum management resource of plundering method for detecting like this, and then realize the fastest emergency response that the reply crime takes place.

Description of drawings

Be described further below in conjunction with the accompanying drawing specific embodiments of the invention:

Fig. 1 is the flow chart of steps that the present invention plunders method for detecting;

Fig. 2 is the flow chart of steps that the present invention plunders the optimum embodiment of method for detecting;

Fig. 3 is the left arm binaryzation synoptic diagram that the present invention plunders template zone in the method for detecting;

Fig. 4 is the right arm binaryzation synoptic diagram that the present invention plunders template zone in the method for detecting;

Fig. 5 is the outside vertical distance of the present invention's left and right sides arm of plundering method for detecting and the horizontal range synoptic diagram between the inboard arm of the left and right sides;

Fig. 6 is a kind of structured flowchart of dispatching framework based on the early warning of cloud of the present invention.

Embodiment

By shown in Figure 1, plunder method for detecting, the step of this method comprises:

S1, the video monitoring picture is obtained;

S2, employing background elimination method are carried out cutting apart of prospect and background to the video monitoring picture that obtains, and then are obtained the background elimination chart;

S3, the background elimination chart is carried out the area-of-interest boundary definition, and then obtain effective area-of-interest;

Comparing to effective area-of-interest in the template zone that S4, basis prestore, and then draws arm comparison result in the left and right sides in effective area-of-interest;

S5, left and right sides arm comparison result is verified, and then obtained effective left and right sides arm comparison result.

Because when plundering generation; The robber can coerce people two, and thereby arms up prevents that people are by alarm bell or make a phone call to report to the police; So just cause the police to rush for rapidly plundering on-the-spot and grab by the robber; So two arms up that this physical characteristic is discerned to people by using this method; Even people are coerced by the robber that two arms up like this, people still can be by lifting high both hands and then warning.

Said by Fig. 2, the optimum embodiment of robbery method for detecting, its step comprises:

S1, the video monitoring picture is obtained;

S21, employing median method generate the reference background picture;

S22, the difference of getting current video monitored picture and reference background picture, and described difference taken absolute value;

S23, said absolute value is carried out binaryzation, and then obtain the background elimination chart of binaryzation according to threshold value;

S24, employing morphology carry out denoising to the background elimination chart of binaryzation.

S31, employing pixel vertical projection and pixel level projection are carried out the area-of-interest boundary definition to the background elimination chart;

S32, the boundary definition scope of area-of-interest is outwards expanded, and then obtained effective area-of-interest according to the border preset value;

S4, employing scan mode are compared to effective area-of-interest based on the template zone that prestores; And then draw arm comparison result in the left and right sides in effective area-of-interest; The said template zone that prestores is through gathering video monitoring picture and then left arm binary map that is partitioned into and right arm binary map, like Fig. 3 and shown in Figure 4;

S51, calculate in effective area-of-interest the left arm degree of approximation measured value of left arm in the left arm comparison result and template zone, and calculate in effective area-of-interest the effectively right arm degree of approximation measured value of right arm comparison result and the regional right-of-center in political views's arm of template;

S52, left arm degree of approximation measured value and right arm degree of approximation measured value are carried out addition, and then obtain the left and right sides arm degree of approximation and measure additive value;

S53, according to degree of approximation measurement threshold, judge that whether the left and right sides arm degree of approximation measure additive value greater than degree of approximation measurement threshold, if, execution in step S54; Otherwise, then get rid of left and right sides arm comparison result;

S54, to carrying out left and right sides arm position judgment in the arm comparison result of the left and right sides, pre-conditioned if the horizontal range between the outside vertical of left and right sides arm distance and the left and right sides inboard arm all meets, then export effective left and right sides arm comparison result; Otherwise, then get rid of left and right sides arm comparison result.

Adopt median method to generate the reference background picture among the above-mentioned steps S21, it is specially if two picture that arms up is the K frame, and promptly the reference background picture is just got the intermediate value of K-1 frame and K-Δ T frame.

Above-mentioned steps S23 carries out binaryzation according to threshold value to said absolute value and then obtains the background elimination chart of binaryzation, and it is specially according to threshold value, judges that whether absolute value is greater than threshold value; If; Then this absolute value is judged as foreground pixel, and this absolute value is carried out binaryzation, puts 1; Otherwise then this absolute value is judged as background pixel, and this absolute value is carried out binaryzation, puts 0.

Adopt the pixel vertical projection that the background elimination chart is carried out area-of-interest left and right sides boundary definition among the above-mentioned steps S31; And adopt the pixel level projection that the background elimination chart is carried out the area-of-interest up-and-down boundary and define, foreground pixel accounts for more than 95% in the pixel of area-of-interest.

Above-mentioned steps S32 be in order to ensure foreground pixel all in area-of-interest, and said step S32 is specially, according to the border preset value; The boundary definition up and down of area-of-interest is all outwards expanded with the border preset value; For example if the border preset value is 3, promptly left margin defines and is moved to the left 3, and right margin defines and moves right 3; The coboundary is defined and is moved up 3, and lower boundary defines and moves down 3.Said border preset value can be a plurality of, respectively corresponding upper and lower, left and right boundary definition.

The computing formula of left arm degree of approximation measured value and calculating right arm degree of approximation measured value is following among the above-mentioned steps S52:

$\left\{\begin{array}{c}{s}_1=w_F\·\mathrm{Area}(X_F\∩T_F)+w_B\·\mathrm{Area}(X_B\∩T_B)\\ s_2=w_F\·\mathrm{Area}(X_F\∩T_B)+w_B\·\mathrm{Area}(X_B\∩T_F)\\ \mathrm{SM}=s_1-s_2\end{array}\right.$

Wherein, W _FAnd W _BBe weighting coefficient, X _BRepresent the background pixel in effective area-of-interest, T _BBackground pixel in the representation template zone, when calculating left arm degree of approximation measured value, X _FRepresent the left arm foreground pixel in effective area-of-interest, T _FLeft arm foreground pixel in the representation template zone, SM are represented left arm degree of approximation measured value; When calculating right arm degree of approximation measured value, X _FRepresent the right arm foreground pixel in effective area-of-interest, T _FRight arm foreground pixel in the representation template zone, SM are represented right arm degree of approximation measured value.

And W _FAnd W _BComputing formula be:

$\left\{\begin{array}{c}{w}_F=\mathrm{Area}\left(T_F\right)/(\mathrm{Area}\left(T_F\right)+\mathrm{Area}\left(T_B\right))\\ w_B=\mathrm{Area}\left(T_B\right)/(\mathrm{Area}\left(T_F\right)+\mathrm{Area}\left(T_B\right))\end{array}\right.$

Likewise, T _BBackground pixel in the representation template zone, when calculating left arm degree of approximation measured value, T _FLeft arm foreground pixel in the representation template zone; When calculating right arm degree of approximation measured value, T _FRight arm foreground pixel in the representation template zone.

It is as follows pre-conditioned that horizontal range among the above-mentioned steps S54 between the outside vertical of left and right sides arm distance and the left and right sides inboard arm meets:

$\left\{\begin{array}{c}{d}_{\mathrm{Ver}}\≤K_1\·{\stackrel{\‾}{d}}_{\mathrm{Ver}}\\ K_2\·{\stackrel{\‾}{d}}_{\text{Hor}}\≤d_{\mathrm{Hor}}\≤K_3\·{\stackrel{\‾}{d}}_{\mathrm{Hor}}\end{array}\right.$

Wherein as shown in Figure 5, d _VerThe outside vertical distance of expression left and right sides arm, d _HorHorizontal range between the inboard arm of the expression left and right sides,

The mean value or the reference value of the outside vertical distance of expression left and right sides arm,

The mean value or the reference value of the horizontal range between the expression left and right sides inboard arm, K1, K2, K3 are constant, and the value of K1 and K3 is greater than 1, and the value of K2 is less than 1.

As shown in Figure 6, a kind of early warning scheduling framework based on cloud comprises:

Monitor video shooting end is used to obtain the video monitoring picture, and the video monitoring picture is sent to early warning dispatching system and Surveillance center's end based on cloud;

Early warning dispatching patcher based on cloud; Be used for the geographical position that the video monitoring picture receives and shooting is held to monitor video is obtained; After adopting the robbery method for detecting that the video monitoring picture that receives is discerned; Hold to Surveillance center based on effective left and right sides arm comparison result that recognizes and then transmission information; And confirmation received the police strength resource table search that mate based on the geographical position of monitor video shooting end the back, and then coupling police strength resource table sends to police station's end to transferring display end after obtaining coupling police strength resource table after preferred police strength resource table is received;

Surveillance center's end; Be used for information and video monitoring picture are received and send confirmation to the early warning dispatching system based on cloud; After the staff of Surveillance center's end finds information, will further confirm whether to have to plunder and take place, then send confirmation to early warning dispatching system based on cloud if having; Then abandon this alarm if not;

Transfer display end; Be used for coupling police strength resource table is received and shows; And confirm the responding scheme of optimizing and then revise coupling police strength resource table through the center leader of police station; Obtain preferred police strength resource table; Preferred police strength resource table is sent to the early warning dispatching patcher based on cloud, also can show preferred police strength resource table simultaneously;

Police station's end is used for preferred coupling police strength resource table is received.Said police station end carries out the police strength allotment according to the preferred coupling police strength resource table that receives, thereby rushes for the robbery crime scene apace, reaches quick emergency response.

Further as preferred embodiment, said early warning dispatching system based on cloud comprises:

Subsystem is plundered in cloud monitoring, is used for the video monitoring picture obtained and adopt plundering method for detecting the video monitoring picture being discerned, according to the effective left and right sides arm comparison result that recognizes and then send information and hold to Surveillance center;

Information scheduler subsystem; Be used for the geographic position that the video monitoring picture receives and shooting is held to monitor video is obtained; Send the load balancing of weighted information according to video monitoring picture and monitor video shooting end to cloud computing platform; And then the load balancing of cloud computing platform is that information processing is carried out with the server that idle degree optimization cooperates in cloud monitoring robbery subsystem searching geographic position; Saidly carry out information processing and be and adopt plunder method for detecting and discern; Therefore adopt dotted line to connect information scheduler subsystem and cloud monitoring robbery among Fig. 6; It means both is not that immediate data connects but relevant, and the server that the geographic position cooperates with idle degree optimization just from monitor video shooting end distance from nearest and idle server, cloud is monitored the robbery subsystem and can be obtained the video monitoring picture in the short time and handle like this; Thereby can rationally utilize computer hardware resource and improve the speed and whole alarm response speed that subsystem identification video monitored picture is plundered in the cloud monitoring

And, will mate the police station geographic position and send to responding scheduler subsystem leaving the shortest coupling police station geographic position of distance, geographic position that monitor video is made a video recording and held according to the police station's geographic position search that prestores after holding the affirmation information that transmits to receive by Surveillance center;

Responding scheduler subsystem; Be used for coupling police station geographic position is received; Real-time police strength resource table search and coupling police station geographic position corresponding coupling police strength resource table according to storage; And then obtain to send coupling police strength resource table to transferring display end behind the coupling police strength resource table, after being received, preferred police strength resource table sends to police station's end;

Said information scheduler subsystem discharges shared resource and shared resource given cloud computing platform when wait acknowledge information scheduling of resource process.

More than be that preferable enforcement of the present invention is specified; But the invention is not limited to said embodiment; Those of ordinary skill in the art make all equivalent variations or replacement under the prerequisite of spirit of the present invention, also can doing, and distortion that these are equal to or replacement all are included in the application's claim institute restricted portion.

Claims (10)

1. robbery method for detecting, it is characterized in that: the step of this method comprises:

S1, the video monitoring picture is obtained;

S2, employing background elimination method are carried out cutting apart of prospect and background to the video monitoring picture that obtains, and then are obtained the background elimination chart;

S3, the background elimination chart is carried out the area-of-interest boundary definition, and then obtain effective area-of-interest;

Comparing to effective area-of-interest in the template zone that S4, basis prestore, and then draws arm comparison result in the left and right sides in effective area-of-interest;

S5, left and right sides arm comparison result is verified, and then obtained effective left and right sides arm comparison result.

2. according to the said robbery method for detecting of claim 1, it is characterized in that: said step S2 comprises:

S21, employing median method generate the reference background picture;

S22, the difference of getting current video monitored picture and reference background picture, and described difference taken absolute value;

S23, said absolute value is carried out binaryzation, and then obtain the background elimination chart of binaryzation according to threshold value;

S24, employing morphology carry out denoising to the background elimination chart of binaryzation.

3. according to the said robbery method for detecting of claim 1, it is characterized in that: said step S3 comprises:

S31, employing pixel vertical projection and pixel level projection are carried out the area-of-interest boundary definition to the background elimination chart;

S32, the boundary definition scope of area-of-interest is outwards expanded, and then obtained effective area-of-interest according to the border preset value.

4. according to the said robbery method for detecting of claim 3, it is characterized in that: adopt the pixel vertical projection background elimination chart is carried out area-of-interest left and right sides boundary definition and to adopt the pixel level projection that the background elimination chart is carried out the area-of-interest up-and-down boundary and define among the said step S31.

5. according to the said robbery method for detecting of claim 1, it is characterized in that: said step S4 adopts scan mode according to the template zone that prestores effective area-of-interest to be compared one by one, and then draws arm comparison result in the left and right sides in effective area-of-interest.

6. according to the said robbery method for detecting of claim 1, it is characterized in that: said step S5 comprises:

S51, calculate in effective area-of-interest the left arm degree of approximation measured value of left arm in the left arm comparison result and template zone, and calculate in effective area-of-interest the effectively right arm degree of approximation measured value of right arm comparison result and the regional right-of-center in political views's arm of template;

S52, left arm degree of approximation measured value and right arm degree of approximation measured value are carried out addition, and then obtain the left and right sides arm degree of approximation and measure additive value;

S53, according to degree of approximation measurement threshold, judge that whether the left and right sides arm degree of approximation measure additive value greater than degree of approximation measurement threshold, if, execution in step S54; Otherwise, then get rid of left and right sides arm comparison result;

S54, to carrying out left and right sides arm position judgment in the arm comparison result of the left and right sides, pre-conditioned if the horizontal range between the outside vertical of left and right sides arm distance and the left and right sides inboard arm all meets, then export effective left and right sides arm comparison result; Otherwise, then get rid of left and right sides arm comparison result.

7. according to the said robbery method for detecting of claim 6, it is characterized in that: the computing formula of left arm degree of approximation measured value and calculating right arm degree of approximation measured value is following among the step S52:

Wherein, W _FAnd W _BBe weighting coefficient, X _BRepresent the background pixel in effective area-of-interest, T _BBackground pixel in the representation template zone, when calculating left arm degree of approximation measured value, X _FRepresent the left arm foreground pixel in effective area-of-interest, T _FLeft arm foreground pixel in the representation template zone, SM are represented left arm degree of approximation measured value; When calculating right arm degree of approximation measured value, X _FRepresent the right arm foreground pixel in effective area-of-interest, T _FRight arm foreground pixel in the representation template zone, SM are represented right arm degree of approximation measured value.

8. according to the said robbery method for detecting of claim 6, it is characterized in that: it is as follows pre-conditioned that the horizontal range among the said step S54 between the outside vertical of left and right sides arm distance and the left and right sides inboard arm meets:

D wherein _VerThe outside vertical distance of expression left and right sides arm, d _HorHorizontal range between the inboard arm of the expression left and right sides, the mean value or the reference value of the outside vertical distance of expression left and right sides arm, the mean value or the reference value of the horizontal range between the inboard arm of the expression left and right sides, K ₁, K ₂, K ₃Be constant.

9. adopt a kind of early warning scheduling framework of the said robbery method for detecting of arbitrary claim in claim 1 to the claim 8, it is characterized in that: comprising based on cloud:

Monitor video shooting end is used to obtain the video monitoring picture, and the video monitoring picture is sent to early warning dispatching system and Surveillance center's end based on cloud;

Early warning dispatching patcher based on cloud; Be used for the geographical position that the video monitoring picture receives and shooting is held to monitor video is obtained; After adopting the robbery method for detecting that the video monitoring picture that receives is discerned; Hold to Surveillance center based on effective left and right sides arm comparison result that recognizes and then transmission information; And confirmation received the police strength resource table search that mate based on the geographical position of monitor video shooting end the back, and then obtain to send coupling police strength resource table to transferring display end behind the coupling police strength resource table, after being received, preferred police strength resource table sends to police station's end;

Surveillance center's end is used for information and video monitoring picture are received and send confirmation to the early warning dispatching system based on cloud;

Transfer display end, be used for coupling police strength resource table is received and shows, and send preferred police strength resource table to early warning dispatching system based on cloud;

Police station's end is used for preferred coupling police strength resource table is received.

10. a kind of early warning scheduling framework according to claim 9 based on cloud, it is characterized in that: said early warning dispatching system based on cloud comprises:

Subsystem is plundered in cloud monitoring, is used for the video monitoring picture obtained and adopt plundering method for detecting the video monitoring picture being discerned, according to the effective left and right sides arm comparison result that recognizes and then send information and hold to Surveillance center;

Information scheduler subsystem; Be used for the geographical position that the video monitoring picture receives and shooting is held to monitor video is obtained; Send the load balancing of weighted information based on video monitoring picture and monitor video shooting end to cloud computing platform; And then the load balancing of cloud computing platform is that information processing is carried out with the server that empty limit optimization cooperates in cloud monitoring robbery subsystem searching geographical position; And confirmation received the back based on the geographical position distance the shortest coupling police station geographical position of the police station geographical position search that prestores from monitor video shooting end, will mate the police station geographical position and send to responding scheduler subsystem;

Responding scheduler subsystem; Be used for coupling police station geographic position is received; Real-time police strength resource table search and coupling police station geographic position corresponding coupling police strength resource table according to storage; And then obtain to send coupling police strength resource table to transferring display end behind the coupling police strength resource table, after being received, preferred police strength resource table sends to police station's end;

Said information scheduler subsystem discharges shared resource and shared resource given cloud computing platform when wait acknowledge information scheduling of resource process.

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