KR20170001872A - Statistical analysis apparatus and method using pattern analysis in omni-directional camera images - Google Patents

Statistical analysis apparatus and method using pattern analysis in omni-directional camera images Download PDF

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KR20170001872A
KR20170001872A KR1020150091217A KR20150091217A KR20170001872A KR 20170001872 A KR20170001872 A KR 20170001872A KR 1020150091217 A KR1020150091217 A KR 1020150091217A KR 20150091217 A KR20150091217 A KR 20150091217A KR 20170001872 A KR20170001872 A KR 20170001872A
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image
smart
unit
specific object
statistical analysis
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KR101729906B1 (en
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박구만
장지웅
김영애
정지상
박종화
왕기석
김경만
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서울과학기술대학교 산학협력단
주식회사 에보시스
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G08B13/19608—Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19617—Surveillance camera constructional details
    • G08B13/1963—Arrangements allowing camera rotation to change view, e.g. pivoting camera, pan-tilt and zoom [PTZ]
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19654—Details concerning communication with a camera
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B13/00—Burglar, theft or intruder alarms
    • G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
    • G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
    • G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
    • G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
    • G08B13/19665—Details related to the storage of video surveillance data
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B3/00—Audible signalling systems; Audible personal calling systems
    • G08B3/10—Audible signalling systems; Audible personal calling systems using electric transmission; using electromagnetic transmission
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B5/00—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied
    • G08B5/22—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electric transmission; using electromagnetic transmission
    • G08B5/36—Visible signalling systems, e.g. personal calling systems, remote indication of seats occupied using electric transmission; using electromagnetic transmission using visible light sources

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Electromagnetism (AREA)
  • Multimedia (AREA)
  • Image Analysis (AREA)
  • Closed-Circuit Television Systems (AREA)

Abstract

In the present invention, in the case of the conventional CCTV surveillance system, since only a fixed radius is localized, a plurality of cameras must be installed, a rectangular area is generated according to the environment of the surveillance area, There is a problem in that the operation of tracking the object is delayed by the camera due to an increase in the amount of computation for the object and there is no function of transmitting the automatic warning broadcasting according to the situation alarm information generated in the field, The smart omnidirectional camera device 100, the data communication interface unit 200 and the smartimage and statistical analysis server 300. In this case, instead of a plurality of CCTVs installed in one place, The object can be generated as a 360-degree donut-type panoramic image and can be monitored in real time, and the remote smart image / statistical analysis server It is possible to continuously detect and track specific objects that are behaving abnormally in real time continuously without any interruption. It can accumulate moving trajectory patterns of specific objects in real time and select one of image color map and statistical graph, It is possible to control the automatic warning broadcasting to be transmitted according to the event situation of the specific object generated in the field, and it is possible to control only the program in addition to the existing system so that it is compatible with other neighboring smart It is possible to track the position of a specific object in real time by linking with statistical analysis device and ubiquitous sensor network (USN), and it is possible to improve the security effect by omnidirectional camera based on intelligent image analysis technology by 80% To provide a smart statistical analysis apparatus and method using the moving trajectory pattern analysis To have its purpose.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a smart statistical analysis apparatus and a method for analyzing a moving trajectory pattern in an omnidirectional camera image,

In the present invention, instead of a plurality of CCTVs installed in one place, a 360-degree donut-type omnidirectional image can be generated with one camera and real-time monitoring can be performed. It is possible to continuously detect and track a specific object in real time continuously without interruption and to accumulate moving trajectory pattern of a specific object in real time to select one of image color map and statistical graph to display statistical analysis report by place and time And more particularly, to an apparatus and method for smart statistical analysis using motion trajectory pattern analysis in an omnidirectional camera image.

Recently, due to the frequent occurrence of violent crime, social anxiety has increased and interest in individuals and public safety has increased.

For this reason, the importance of the development and application of video surveillance system for prevention, post-analysis and quick resolution of crime is increasing.

In image surveillance system, image quality improvement, image transmission and storage technology have developed much more than in past systems.

 Also, by developing a network camera connected to the Internet, it is possible to perform video surveillance remotely.

These systems are widely applied to the peripheral technology, and as the price is relatively low, it is possible to widely distribute the effective video surveillance system.

 CCTV (Closed Circuit Television) is installed in a place requiring security such as a public place, a hunting area, and an access control area using a wide-area camera, and the screen image is directly monitored by the monitoring personnel or recorded in a storage device, And the like.

However, since the conventional CCTV surveillance system only performs local area surveillance for a fixed radius, a large number of cameras must be installed for a wide area surveillance, and a rectangular area is generated depending on the environment of the surveillance area.

In addition, even if a plurality of CCTV cameras are installed, there is a problem that the operation amount of the CCTV cameras is interlocked and the operation schedule is increased, so that the operation of tracking the object by the camera is delayed.

In addition, in the case of a conventional CCTV camera, there is a problem that it is impossible to prevent a criminal act in advance because there is no function of transmitting an automatic warning broadcast according to situation alarm information generated in the field.

Korean Patent Registration No. 10-1360246

In order to solve the above problems, instead of a plurality of CCTVs installed in one place, an object can be generated as a 360-degree donut-type omni-directional image with a single camera and can be monitored in real time, The analysis server can continuously detect and track specific objects that are behaving abnormally in real time continuously without interruption and select statistical analysis report by selecting one of image color map and statistical graph by accumulating moving trajectory pattern of specific object in real time. The present invention provides an apparatus and method for smart statistical analysis using motion trajectory pattern analysis in omnidirectional camera images that can be displayed by place and time zone.

In order to achieve the above object, a smart statistical analysis apparatus using motion trajectory pattern analysis in an omnidirectional camera image according to the present invention comprises:

The identification ID is set and the object is photographed 360 degrees in all directions with one camera while being located at a specific place and then the taken donut type omni-directional image is transmitted to the remote smart image / statistical analysis server through the data communication interface unit A smart omnidirectional camera device 100 for receiving a response signal according to an event of a specific object,

A data communication interface unit 200 for connecting the smart omnidirectional camera device and the smart image / statistical analysis server to each other through wired / wireless communication lines to form a bidirectional data communication network,

And a data communication interface unit for receiving a donut-type omnidirectional image transmitted from the smart omnidirectional camera device to convert the imaged omnidirectional image, detecting a specific object, tracking the position of the specific object based on the movement trajectory pattern of the specific object, And a smart image / statistical analysis server 300 for accumulating moving trajectory patterns of the objects in real time and displaying the statistical analysis reports according to places and time zones.

As described above, in the present invention,

First, in place of installing a plurality of CCTVs in one place, a 360 ° donut type omnidirectional image can be generated and monitored in real time by a single camera, so that the surveillance range can be improved by 70% The installation cost can also be reduced by 80% compared to the existing one.

Secondly, the distorted image of the rectangular panoramic image conversion unit can be corrected through the image distortion correction unit, the image quality can be improved, and a high-quality image can be provided.

Third, after detecting a specific object, it is possible to track the position of the ideal object based on the movement trajectory pattern of the specific object and to control the automatic warning broadcast according to the event situation of the specific object generated in the field, The crime rate can be reduced by 70%.

Fourth, it is possible to interoperate only the program in addition to the existing system, and it is excellent in compatibility.

Fifth, the moving trajectory pattern of a specific object can be stacked in real time, and the statistical analysis report can be displayed in each place and time zone by selecting one of the image color map and the statistical graph, and the whole security effect based on the intelligent image analysis technology Can be improved by 80%.

FIG. 1 is a block diagram showing components of a smart statistical analysis apparatus 1 using an analysis of a moving trajectory pattern in an omnidirectional camera image according to the present invention.
FIG. 2 is a block diagram showing components of a smart omnidirectional camera device according to the present invention;
FIG. 3 is a perspective view showing an outer appearance of an omnidirectional camera module including a lens unit and a parabolic reflector according to the present invention,
FIG. 4 is a block diagram illustrating the components of the omnidirectional camera module according to the present invention.
FIG. 5 is a block diagram illustrating components of a smart image / statistical analysis server according to the present invention.
FIG. 6 is a block diagram illustrating components of a rectangular panoramic image conversion unit according to the present invention.
FIG. 7 is a block diagram showing a configuration of a 4-channel image converting unit according to the present invention;
8 is a diagram illustrating an embodiment of converting a donut-type omni-directional image into a rectangular panoramic image having four channels by using a coordinate transformation formula through a four-channel image conversion unit according to the present invention.
FIG. 9 is a diagram illustrating an embodiment of mapping a pixel value in the nearest position among a total of nine pixel values calculated through the coordinate operation unit in the 9-point interpolation algorithm engine unit according to the present invention.
FIG. 10 is a block diagram showing the components of the smart control unit according to the present invention.
11 is a diagram illustrating a histogram of the distribution of brightness of a local region through a HOG object detection unit according to an embodiment of the present invention,
FIG. 12 is a diagram illustrating an object moving trajectory analyzing unit according to an embodiment of the present invention that detects an object in a real-time input image using a Gaussian Mixture Model and extracts a noise-canceled foreground image using a morphology operation In an embodiment showing a result screen,
FIG. 13 is a diagram illustrating an example of accumulating movement trajectories of an object movement trajectory analysis unit according to the present invention.
14A is a diagram illustrating a result of a heat map (calculated in units of 10 minutes) in a binary image calculated through an accumulation value of each pixel through an object movement trajectory analysis unit according to an embodiment of the present invention.
FIG. 14B is a diagram illustrating a result of a heat map expressed in a background image to be displayed to a user through an object movement trajectory analysis unit according to an embodiment of the present invention.
FIG. 15 is a diagram illustrating a result of a heat map 30 minutes after the beginning of an image analysis expressed in a background image of a divided image to be displayed to a user through an object movement trajectory analysis unit according to the present invention.
FIG. 16 is a graph showing the result of a graph obtained in 10-minute increments based on the start of image analysis through the object movement trajectory analysis unit according to the present invention.
17 is a block diagram showing the components of the statistical analysis control unit according to the present invention,
FIG. 18 is a block diagram showing the components of the movement trajectory accumulation forming unit according to the present invention,
FIG. 19 is a diagram illustrating an example of accumulating movement trajectories of a specific object through the moving trajectory accumulation forming unit according to the present invention.
20 shows an embodiment showing accumulating pixels through the first accumulation mode of the moving trajectory accumulation forming unit according to the present invention,
FIG. 21 is a diagram illustrating accumulation of pixels through the second accumulation mode of the moving trajectory accumulation forming unit according to an embodiment of the present invention.
22 is a diagram illustrating accumulation of pixels through the third accumulation mode of the trajectory accumulation forming unit according to the present invention,
FIG. 23 is a diagram illustrating a method of actually accumulating pixel units in a third cumulative formation mode of the moving trajectory accumulation forming unit according to the present invention,
FIG. 24 shows an embodiment in which each RGB channel is allocated and configured in the JET spectrum through the JET spectrum color distribution unit 344a-4 according to the present invention,
25 shows an embodiment showing the display of a color map on an image through the image color map type exposing unit 344b according to the present invention,
FIG. 26 is a diagram illustrating a second statistical analysis report formed by an RGB statistic graph by accumulating specific object movement trajectory information in real time through a statistical graphical display unit according to the present invention,
27 is a flowchart showing a smart statistical analysis method using an analysis of a moving trajectory pattern in an omnidirectional camera image according to the present invention.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram illustrating components of a smart statistical analysis apparatus 1 using an analysis of a moving trajectory pattern in an omnidirectional camera image according to the present invention, which includes a smart omnidirectional camera apparatus 100, (200), and a smart image / statistical analysis server (300).

First, the smart omnidirectional camera device 100 according to the present invention will be described.

The smart omnidirectional camera device 100 sets an identification ID and is located at a specific place and photographs a specific object 360 degrees in all directions with one camera. Then, the smart omnidirectional omnidirectional image is photographed through a data communication interface unit, · It transmits statistics broadcasting to the statistical analysis server, receives the response signal, and sends alarm broadcasting according to the event condition of a specific object.

2, the main body 110 includes a main body 110, an omnidirectional camera module 120, a speaker 130, and a toroidal omni-directional image transmitter 140.

First, the main body 110 according to the present invention will be described.

The main body 110 is formed in a longitudinal dome structure to protect and support each device from external pressure.

Second, the omnidirectional camera module 120 according to the present invention will be described.

The omnidirectional camera module 120 is positioned on the head of the main body, and serves to create a donut-type omnidirectional image.

As shown in FIGS. 3 and 4, the CCD sensor unit 123 includes a lens unit 121, a parabolic reflector 122, and a CCD sensor unit 123.

The lens unit 121 serves to introduce the light coming from the 360 degree field of view into the parabolic reflector.

As shown in FIG. 3, one aspheric surface single optical lens capable of wide-angle photographing is formed on one side of an inner space of a body formed of a longitudinal dome structure.

The lens unit 121 is configured to perform a coating design considering the surface of the lens and the coating jig.

The parabolic reflection plate 122 reflects light from the lens unit to the CCD sensor unit.

This forms an AR coating on the surface.

Here, the AR coating removes the infrared region band to prevent light saturation, thereby increasing the transmittance of the lens.

Using the coherence of light, it improves the transmission characteristic in a desired wavelength region by attaching a film having a thickness smaller than the wavelength.

The CCD sensor unit 123 focuses the light reflected from the parabolic reflector to generate a donut-shaped panoramic image.

This is a device that converts light into an electrical signal. Since the charges generated in the light receiving part sequentially move through the MOS capacitors connected in series, the voltage changes from the source follower to the voltage, so a high voltage power source is used.

A separate chip is included in the light receiving unit.

The CCD sensor unit according to the present invention may cause incidence of whitening and smear due to incidence of an excessive amount of light.

In order to prevent this, a filter for blocking infrared rays in the vicinity of 650 nm to 1500 nm is used.

As an infrared cut filter, an IR cut filter and an IR absorption filter are constituted.

The IR cut filter is formed by an optical coating method and generates a wavelength shift according to an incident angle, thereby blocking infrared rays.

The IR absorption filter serves to absorb an infrared wavelength.

Third, the speaker unit 130 according to the present invention will be described.

The speaker unit 130 is driven according to a control signal of the smart image / statistical analysis server and transmits a warning broadcast according to an event condition of a specific object.

This is because a first event mode in which a warning sound is transmitted to the surroundings together with a voice message indicating "thief" when the event situation of a specific object is an event related to the theft and theft, A second event mode in which a warning sound is transmitted to the surroundings together with a voice event that "an external person has entered", and a second event mode in which when the event situation of a specific object is an event related to sexual crime, Quot ;, and a third event mode in which a warning sound is transmitted to the surroundings is selected and transmitted.

Fourth, the toroidal omnidirectional image transmission unit 140 according to the present invention will be described.

The donut-type omnidirectional image transmitting unit 140 is located at one side of the inner space of the main body, and is connected to the data communication interface unit to transmit a donut-type omnidirectional image captured by the omnidirectional camera module.

Next, the data communication interface unit 200 according to the present invention will be described.

The data communication interface unit 200 forms a bidirectional data communication network by connecting a smart omnidirectional camera device and a smart image / statistical analysis server through wired / wireless communication lines.

This is configured by selecting either a WiFi communication interface, an RS 485 communication interface, or an RS 232 communication interface.

Next, the smart image and statistical analysis server 300 according to the present invention will be described.

The smart image and statistical analysis server 300 is connected to the data communication interface unit and receives a donut type omni-directional image transmitted from the smart omnidirectional camera device, converts the received image into an image, detects a specific object, It traces the location of a specific object based on criteria and accumulates moving trajectory pattern of a specific object in real time, thereby displaying statistical analysis report by place and time zone.

5, the apparatus includes a donut type panoramic image receiving unit 310, a rectangular panorama image converting unit 320, an image distortion correcting unit 330, and a smart control unit 340.

First, a description will be given of a donut type omnidirectional image receiving unit 310 according to the present invention.

The donut type omnidirectional image receiving unit 310 is connected to the data communication interface unit and receives the donut type omnidirectional image transmitted from the smart omnidirectional camera device.

Second, the rectangular panorama image converting unit 320 according to the present invention will be described.

The rectangular panorama image converting unit 320 transforms the donut type panorama image received from the donut type panorama image receiving unit into a panorama image of a rectangle by performing panorama unrolling.

As shown in FIG. 6, the image forming apparatus includes a 4-channel image converting unit 321, a coordinate calculating unit 322, and a lookup table generating unit 323.

[Four-Channel Image Conversion Unit 321]

The 4-channel image conversion unit 321 converts the donut-type panoramic image data into a 4-channel rectangular panoramic image using a coordinate conversion formula.

This traces the concentric circle line of each pixel of the toroidal omni-directional image to form a coordinate mapping relationship between the toroidal omni-directional image and the rectangular panoramic image.

That is, FIG. 7 is a block diagram illustrating a configuration of a 4-channel image converting unit according to the present invention, wherein R denotes a radius of an inner circle, and 2R denotes a donut-type omnidirectional image having a radius of an outer circle.

An area between the inner radius R and the outer radius 2R indicates a portion where the actual image information exists.

As shown in Fig. 8, the donut-type omnidirectional image is converted into a rectangular panoramic image composed of four channels using a coordinate conversion formula.

The mapping relation between the donut type panorama image and the rectangular panorama image exists in a transformation relation from the polar coordinate system to the rectangular coordinate system.

The coordinate transformation relation between two images can be represented by the parameters (r i , θ i ) and (U i , V i ) and can be expressed by the following equations (1) and (2).

Figure pat00001

Figure pat00002

The conversion relations between the coordinates (X i , Y i ) and (U i , V i ) of the two images can be expressed by Equations (3) and (4) using Equations (1) and

Figure pat00003

Figure pat00004

Figure pat00005

Figure pat00006

[Coordinate operation unit 322]

The coordinate calculation unit 322 divides the toroidal omnidirectional image data into four regions, one of which is used to calculate coordinates using a coordinate transformation formula, and the remaining three regions have three coordinates And stores it in the lookup table generating unit in advance.

This determines the center coordinate value of the toroidal omnidirectional image, divides the toroidal omnidirectional image into four symmetric regions, divides the corresponding rectangular panoramic image into four regions, And calculate the coordinate value.

If the coordinate value is calculated using Equations (3) and (4), the amount of calculation becomes large and the hardware complexity becomes very large.

At this time, in the present invention, the hardware complexity is reduced through the following process, and the realization is realized while reducing the amount of calculation.

First, the center coordinate value of the donut type panoramic image is determined, and the size of the rectangular panoramic image is determined.

Second, the donut-type panoramic image is divided into four symmetric regions, and the corresponding rectangular panoramic image is divided into four regions.

Third, one of the four regions is determined as a calculation region, and coordinate values are calculated using Equations (3) and (4).

Here, the remaining three regions are calculated by the symmetric coordinate method using the calculated coordinate values again, and can be expressed by the following equation (5).

Figure pat00007

Figure pat00008

Figure pat00009

Since the coordinate values of the remaining three areas can be simultaneously calculated through the coordinate calculation unit according to the present invention and the calculation formula is very simple, it is possible to quickly convert the coordinates of the coordinate conversion unit, and the size of the memory used for the look- There is a number.

[Look-up table generating unit 323]

The lookup table generating unit 323 calculates coordinate values between the toroidal omnidirectional image data and the rectangular panoramic image in advance and stores them in a lookup table and stores the lookup table values corresponding to the currently input donut type omnidirectional image data values It plays a role.

This generates LUT_X that stores the value associated with X and LUT_Y that stores the value associated with Y in equations (3) and (4).

The lookup table generating unit 322 is configured by selecting one of 12 bits, 24 bits, and 48 bits in order to use a rectangular panoramic image and to store a decimal point value generated during coordinate conversion.

Further, only a quarter of the rectangular panoramic image size is stored using the symmetry property of the toroidal omnidirectional image.

Third, the image distortion correction unit 330 according to the present invention will be described.

The image distortion correction unit 330 corrects the distorted image of the rectangular panorama image conversion unit and improves the image quality.

This consists of a 9-point interpolation algorithm engine unit that maps 9 pixel values to pixel values nearest to 9 pixel values.

That is, all interpolated pixel values can be calculated as an average of neighboring actual pixel values.

For example, the interpolated pixel value (i, j + 0.5) can be represented by an average value of the actual pixel values (i, j) and (i, j + 1).

The pixel value i + 0.5, j + 0.5 is expressed as an average value of the actual pixel values i, j, i + 1, j, i, j + 1, .

The interpolated pixel value is expressed by the following equation (6).

Figure pat00010

Figure pat00011

Figure pat00012

Figure pat00013

Figure pat00014

The coordinate values calculated through the coordinate calculation unit 220 according to the present invention are mapped to pixel values closest to the nine pixel values.

In Fig. 9, the red triangle is mapped to a value of (i + 0.5, j) in the closest position.

The 9-point interpolation algorithm engine unit according to the present invention can be represented by only two pixel values or an average value of four pixel values.

As described above, the engine part of the 9-point interpolation algorithm can reduce the computational complexity without degrading the quality of the converted panoramic image of the rectangle, and has a very easy characteristic in realizing real-time low-cost hardware.

Fourth, the smart control unit 340 according to the present invention will be described.

The smart control unit 340 detects a specific object on the image-corrected image through the image distortion correction unit, tracks the position of the specific object based on the movement trajectory pattern of the specific object, And controls the display of statistical analysis report by place and time zone.

10, the HOG type object detection unit 341, the object movement trajectory analysis unit 342, the smart object tracking control unit 343, the statistical analysis control unit 344, and the warning broadcast transmission control unit 345 .

[ HOG Type object detection unit 341]

The HOG-type object detection unit 341 detects an object in an image using the Histogram of Gradient (HOG) feature.

As shown in FIG. 11, the distribution direction of the brightness of the local region is expressed by a histogram, and is used as a feature vector, which is suitable for expressing the shape of an object.

In order to obtain the Histogram of Gradient (HOG) feature, it is necessary to first calculate the slope magnitude value and the directional value.

Assuming that the brightness value of each pixel is f (i, j), the slope magnitude m (i, j) and the direction? (I, j) are expressed by Equation (7).

Figure pat00015

Figure pat00016

Figure pat00017

Figure pat00018

If a slope size and directional information are known, a directional histogram for the brightness change of a cell region composed of 8x8 pixel regions can be calculated.

Considering only the directionality of the tilt magnitude, θ (i, j) is divided into 20 ° intervals of 0 ° to 180 °, and 9 directions per cell are used to calculate m (i, j) And is configured to have a histogram Bin (Bin).

Then, the gradient magnitude values are accumulated in each histogram bin to calculate the distribution.

Also, one block includes 3 x 3 cells, and each block is configured to normalize.

Since there are nine directional histogram bins in one cell and nine cells in one block, the number of histogram bins in one block is 81. The feature values for each block are calculated while sliding one cell in the scanning direction.

For each block, the feature p is normalized using the following equation (8).

Figure pat00019

Here, k is the number of features in the block, and ε is set to 1 to prevent calculation failure when the denominator becomes zero.

[Object movement locus analyzer 342]

The object movement trajectory analysis unit 342 removes the background of the object among the objects detected by the HOG type object detection unit and then analyzes the repetitive movement trajectory information of the specific object related to the abnormal behavior, .

Specific objects related to abnormal behavior, person, and vehicle among the objects are newly appearing and disappearing on the screen in the image, and numerous position shifts occur.

Accordingly, in the object movement trajectory analyzing unit according to the present invention, specific objects related to abnormal behavior, people, and vehicles should be assigned to each unique ID through labeling, and each object should be tracked.

Certain objects with unique IDs will lose their unique ID if they disappear from the image or if tracking fails.

At this time, in the object movement trajectory analysis unit according to the present invention, if the same specific object fails to be traced in the middle, it is recognized as a new specific object and a new ID is given.

FIG. 12 is a diagram illustrating an object moving trajectory analyzing unit according to an embodiment of the present invention that detects an object in a real-time input image using a Gaussian Mixture Model and extracts a noise-canceled foreground image using a morphology operation And also to an embodiment showing a result screen.

Next, in order to analyze the movement trajectory of a specific object, a space in which a specific object is located is set in advance.

The location of a particular object means the pixel location in the image.

The object movement trajectory analysis unit according to the present invention performs tracking using the location, size, and type information of a specific object performed through the smart object tracking control unit, and stores the trajectory information until the tracking fails.

FIG. 13 is a diagram illustrating an accumulation of movement trajectories through an object movement trajectory analysis unit according to an embodiment of the present invention. In FIG. 13, an object 1 entered through a door moves from (a) to (b) (C) as shown in Fig.

The motion trajectory is obtained by continuously connecting the blob center blocks of each calculated frame, and the movement trajectory of the object is calculated by connecting the center of the foreground portion through the same result as (c).

The trajectory is a straight line because it is the connection between the center coordinates of the object.

Therefore, in the present invention, the Bezier curve method of approximating the curve shape is applied.

The Bezier curve is an n-th order curve obtained from n points, and a curve of a cubic Bezier is used as shown in Equation (9) below to generate a smooth curve.

Figure pat00020

Figure pat00021

The object movement trajectory analysis unit 342 according to the present invention uses trajectory of the third order bezier to make trajectory of a straight line shape into smooth trajectory, accumulates trajectory information about a specific object, Thereby constituting a heat map.

For example, in the present invention, binary images of one frame per second are accumulated in consideration of the image size of an omnidirectional camera module of at least 3 Megapixels and the amount of computation required for image analysis, and cumulative values of trajectories are calculated based on a maximum of one hour.

For example, if the heat map is accumulated one time per second, the maximum is 3600 for one hour.

If the color map is divided by 360, which is the value of the color map, the heat map has a color map value of 10 units.

The heat map calculated in units of 10 minutes by applying this is shown in FIG.

FIG. 14 (a) relates to an embodiment showing a heat map result in a binary image calculated through the cumulative value of each pixel, and FIG. 14 (b) And in one embodiment showing a heat map result.

FIG. 15 is a diagram showing an example of a heat map result 30 minutes after the start of image analysis expressed by being displayed on a background image of a divided image to show to a user.

As described above, when the image is represented by a color map through the object movement trajectory analyzing unit 420 according to the present invention, it is possible to express at which position the movement trajectory is large.

However, it is difficult to know whether there are a lot of specific objects at a certain time in the place where the camera is installed as a heat map which expresses colors in the image.

Therefore, it is possible to provide the analysis data about the number of the floating population at a certain time by expressing the information which is difficult to express by the color map.

FIG. 16 is a diagram illustrating graphical results obtained in units of 10 minutes based on the start of image analysis through the object movement trajectory analysis unit according to the present invention. Since the graph is also a connection between integer values, see.

Therefore, the Bezier curve method is applied to approximate this to a curve shape.

The results of the graph using the Bezier curves show that the floating population was the largest for 10 minutes after the start of the analysis.

[Smart Object Tracking Control Unit 343]

The smart object tracking control unit 343 is a kernel based tracking system in a hybrid method comprising ROI (Region of Interest) that is a result of detection detected by the HOG type object detection unit and specific object movement trajectory information of the object movement trajectory analysis unit, It traces the object.

In tracking a specific object, there is no restriction according to the tracking form of a specific object, and by using the color information, the tracking characteristic of a specific object is stronger than that of other tracking methods.

Table 1 below is a table describing object tracking result data and contents through the smart object tracking controller according to the present invention.

division all
Number of frames normal
Tracking
Number of frames Tracking
error
Number of frames Tracking
Error rate Number of objects Object tracking Content content of a specific object One 2,456 1,724 20 3.38% 3 Specific objects to escape and roaming specific objects 2 2,645 1,578 5 0.09% 2 Specific objects that run away, and garbage dumping specific objects 3 2,341 2,689 405 13.68% 2 Specific objects to escape 4 2,254 1,360 3 0.07% One Specific objects to roam 5 4,246 3.268 3 0.03% 2 Specific objects to escape 6 3,233 1,889 0 0.00% One Specific objects that are roaming and garbage dumping specific objects 7 2,678 1,934 6 0.03% 3 Garbage speculation specific object 8 2,045 1,105 120 0.54% 2 Garbage speculation specific object 9 2,684 2,689 1523 6.46% One Integrated video in all situations 10 2.540 5,868 255 17.35% 2 Tracking after stopping All errors after the disappearance 11 1.396 2,110 855 10.62% One Recognize errors as stop objects after disappearing from the screen 12 1,389 1,467 241 19.64% 2 An error occurs because the size of the object is less than the minimum size

[Statistical analysis control unit 344]

The statistical analysis control unit 344 controls the smart object tracking control unit 153 to accumulate the specific object movement trajectory information in real time and display the statistical analysis report by place and time zone.

As shown in Fig. 17, this is constituted by a moving locus accumulation forming section 344a, an image color map type display section 344b, and a statistical graph type display section 344c.

The movement trajectory accumulation forming unit 344a accumulates the specific object trajectory information traced through the smart object tracing control unit 153 in real time.

This accumulates the data of a specific object in order to know the movement trajectory of a specific object for image analysis.

In order to accumulate the movement trajectory information of the specific object, the cumulative data of the unit of time and the unit of the day are displayed in order to accumulate the partial pixels passing through the object in the whole image.

The moving trajectory accumulation forming unit according to the present invention includes a first cumulative formation mode 344a-1 for accumulating pixels for all blob pixels by blob tracing by a matching blob method, A second accumulation mode 344a-2 for accumulating a certain block unit by assigning a certain block to the blob center of all the detected objects, and a third accumulation mode 344a-2 for accumulating only the center pixel of the detected object blob (344a-3) are selected and configured.

FIG. 19 is a diagram illustrating an embodiment for accumulating movement trajectories of a specific object through the movement trajectory accumulation forming unit according to the present invention. Referring to FIG. 20, a moving trajectory in which a specific object moves in a first input image and a second input image, FIG. 21 relates to an embodiment showing accumulating pixels through a second accumulation mode, FIG. 22 relates to an embodiment showing accumulation of pixels through a third accumulation mode Lt; RTI ID = 0.0 > pixel < / RTI > mode.

FIG. 23 is a view showing how a pixel is actually accumulated on a pixel-by-pixel basis through the third accumulation mode according to the present invention, in which a certain block in the central portion of the block moves over time Accumulate one pixel for the block.

The initial value of each pixel is initialized to 0, and the central block of the blob accumulates 1 to the past pixels. As the pixel passes through the central block of the blob over time, the cumulative value of the pixel increases do.

If the entire blob is used, the blob is accumulated by 1 based on all the pixels passing by. In the case of using the blob center pixel, the cumulative value is applied to the past pixels according to the movement locus of the central pixel.

These cumulative values are used when a cumulative value of each pixel is converted into a color map in the case where the cumulative value is displayed in a color map by statistical analysis of the moving trajectory.

When representing cumulative data of a moving trajectory on a two-dimensional space, it can be represented by more effective data using color mapping.

The movement locus accumulation forming unit 344a according to the present invention includes a JET spectrum color distribution unit 344a-4, which is mainly used as a color map.

In the JET spectrum of the JET spectrum color distribution unit 344a-4, each RGB channel is allocated and configured as shown in Fig.

That is, the JET spectrum color distribution unit 344a-4 is configured to easily recognize the movement trajectory at a glance.

The part where the movement trajectory of the specific object is not present is not represented by the color but the part where the movement trajectory of the specific object is present but the movement trajectory is the smallest is represented as dark blue having only the blue channel 127, Most places are represented in dark red, so that they can be seen at a glance.

The image color map type display unit 344b accumulates the specific object movement trajectory information tracked by the smart object tracking control unit 153 in real time and displays the first statistical analysis report formed as a color map on the image by location and time zone It plays a role.

This is done by applying an arbitrary threshold to the cumulative value of each pixel in the cumulative database so that the excluded pixel does not process anything except for a value that does not meet this threshold and sets the pixel with the minimum value to dark blue, Is set to dark red, the difference between the minimum value and the maximum value is divided into a predetermined range, and the color map is superimposed on the image in the color of the JET spectrum formed in the JET spectrum color distribution portion.

The image color map type display unit 344b according to the present invention is configured to divide the maximum value from the minimum value of the JET spectrum formed in the JET spectrum color distribution unit by 360 and assign values from 0 to 360. [

25 is a view showing an embodiment of displaying a color map on an image through an image color map type exposing unit 344b according to the present invention, assuming that there is an image having 20x20 pixels, and each pixel The cumulative value of 1 to 15 is simplified.

The threshold value is set to 5 so that no pixel is assigned to the pixel accumulation value having a pixel value of 5 and a color ranging from dark red to dark blue is given to a pixel having a value ranging from 6 to 15, To display a color map on the image.

The statistical graph type display unit 344c displays the second statistical analysis report generated by the RGB statistical graph by place and time by accumulating the specific object movement trajectory information tracked through the smart object tracking control unit 153 do.

This is configured to display the RGB statistic graph calculated in units of time and to display the number of movement trajectories at any time.

The RGB statistical graph calculation method is calculated by calculating the sum of the accumulated data through the movement trajectory analysis in real time and displaying it on the graph.

If there is no specific object moving in the space, the Y axis value of the graph is set to 0, and if there are many moving objects, the Y axis value is set high.

In this case, the Y-axis value of the data is added in units of one hour based on the time of the image analysis server, so that the cumulative value accumulated for one hour is calculated and displayed in a graph.

FIG. 26 is a diagram showing a second statistical analysis report formed by real-time accumulation of specific object movement trajectory information through a statistical graph type display unit according to the present invention and formed by an RGB statistical graph.

[Warning broadcast transmission control unit 345]

The alert broadcast control unit 345 controls the smart object tracking control unit to send a customized warning broadcast signal according to an event situation of a specific object to the smart omnidirectional camera device in the field.

Here, a 1: 1 customized automatic warning broadcast sends a warning message "Catch thieves" when it is a specific object that runs away, and when it is a specific object of garbage dumping, a warning message "Do not dump the garbage ~ In case of a specific object to be roamed, it is configured to send a warning message "This is a place where the security monitoring system is operated, please move to another place ".

Hereinafter, a specific operation process of the smart statistical analysis method using the motion trajectory pattern analysis in the omnidirectional camera image according to the present invention will be described.

First, as shown in FIG. 27, a specific object is photographed 360 degrees in all directions with a single camera through a smart omnidirectional camera device (S100).

Next, the donut type panoramic image taken by the smart panoramic camera device is transmitted to the smart image / statistical analysis server through the data communication interface unit (S200).

Next, the smart image and statistical analysis server receives the donut-type panoramic image transmitted from the smart omnidirectional camera device, detects the specific object by image conversion, and then tracks the position of the specific object based on the movement trajectory pattern of the specific object (S300).

Next, the smart image / statistical analysis server traces the position of a specific object based on the movement trajectory pattern of a specific object, accumulates the movement trajectory pattern of the specific object in real time, and displays the statistical analysis report by place and time zone (S400 ).

Next, the warning broadcast transmission control unit of the smart image / statistical analysis server transmits a customized warning broadcast signal according to the event status of the specific object to the smart omnidirectional camera device in the field (S500).

Finally, the smart omnidirectional camera device receives the warning broadcast signal from the alarm broadcast control unit of the smart image / statistical analysis server and transmits a warning broadcast according to the event status of the specific object (S600).

1: Smart statistical analysis device 100: Smart omnidirectional camera device
110: main body 120: omnidirectional camera module
130: Speaker unit 140: Donut type omnidirectional image transmitter
200: Data communication interface unit 300: Smart image / statistical analysis server
310: a donut type panoramic image receiving unit 320: a rectangular panoramic image converting unit
330: image distortion correction unit 340: smart control unit

Claims (7)

The identification ID is set and the object is photographed 360 degrees in all directions with one camera while being located at a specific place and then the taken donut type omni-directional image is transmitted to the remote smart image / statistical analysis server through the data communication interface unit A smart omnidirectional camera device 100 for receiving a response signal according to an event of a specific object,
A data communication interface unit 200 for connecting the smart omnidirectional camera device and the smart image / statistical analysis server to each other through wired / wireless communication lines to form a bidirectional data communication network,
And a data communication interface unit for receiving a donut-type omnidirectional image transmitted from the smart omnidirectional camera device to convert the imaged omnidirectional image, detecting a specific object, tracking the position of the specific object based on the movement trajectory pattern of the specific object, And a smart image and statistical analysis server (300) for accumulating the movement trajectory pattern of the object in real time and displaying the statistical analysis report by place and time zone. The smart statistical analysis using the trajectory pattern analysis in the omnidirectional camera image Device.
The smart omnidirectional camera system according to claim 1, wherein the smart omnidirectional camera device (100)
A main body 110 formed in a longitudinal dome structure for protecting and supporting each device from external pressure,
An omnidirectional camera module 120 positioned on the head portion of the main body and generating a toroidal omnidirectional image,
A speaker unit 130 positioned at a rear end of the main body and driven according to a control signal of the smart image and statistical analysis server to transmit a warning broadcast according to an event condition of a specific object,
And a donut-type omnidirectional image transmitting unit (140) located at one side of the inner space of the main body and connected to the data communication interface unit to transmit a donut type omnidirectional image taken by the omnidirectional camera module Smart statistical analysis device using motion trajectory pattern analysis.
3. The system of claim 2, wherein the omnidirectional camera module (120)
A lens unit 121 for introducing the light coming from the 360 degree field of view into the parabolic reflector,
A parabolic reflection plate 122 for reflecting the light introduced from the lens unit to the CCD sensor unit,
And a CCD sensor unit (123) that focuses the light reflected from the parabolic reflector to generate a donut type panoramic image.
The system according to claim 1, wherein the smart image / statistical analysis server (300)
A donut type omnidirectional image receiving unit 310 connected to the data communication interface unit and receiving a donut type omnidirectional image transmitted from the smart omnidirectional camera device,
A rectangle panorama image converting unit 320 for converting a donut type panorama image received by the donut type panorama image receiving unit into a panorama image of a rectangle by panorama unrolling,
An image distortion correction unit 330 for correcting the distorted image of the rectangular panorama image conversion unit and improving the image quality,
After detecting a specific object on the image-corrected image through the image distortion correction unit, the position of the specific object is tracked based on the movement trajectory pattern of the specific object, and the movement trajectory pattern of the specific object is accumulated in real time, , And a smart control unit (340) for controlling the smart control unit (340) to control the smart control unit (340) to display the images according to time zones.
The apparatus of claim 4, wherein the rectangular panorama image transform unit (320)
A four-channel image conversion unit 321 for converting a donut-type panoramic image into a rectangular panoramic image composed of four channels using a coordinate conversion formula,
The toroidal omnidirectional image data is divided into four regions, one of which is used to calculate coordinates using a coordinate conversion formula, and the remaining three regions are used to calculate three coordinate values simultaneously using the symmetry property to generate a lookup table A coordinate calculating unit 322 for storing the data in advance,
A lookup table generating unit 323 for calculating coordinate values between the toroidal omnidirectional image data and the rectangular panoramic image in advance and storing them in a lookup table and loading a lookup table value corresponding to the currently input donut type omnidirectional image data value Wherein the motion vector of the camera is determined based on the motion trajectory pattern.
5. The apparatus of claim 4, wherein the smart control unit (340)
An HOG-type object detection unit 341 for detecting an object in an image using a Histogram of Gradient (HOG)
An object movement trajectory analysis unit 342 for analyzing repetitive movement trajectory information of a specific object related to an abnormal behavior, a person, and a vehicle as a result of object detection after removing the background of the object among the objects detected by the HOG type object detection unit, ,
A smart object tracking control unit for tracking a Kernel Based object in a hybrid method comprising ROI (Region of Interest), which is a result of detection by the HOG type object detection unit, and specific object movement trajectory information of the object movement trajectory analysis unit 343,
A statistical analysis control unit 344 for accumulating the specific object movement trajectory information tracked by the smart object tracking control unit 153 in real time and controlling the statistical analysis report to be displayed in each place and time zone,
And a warning broadcast transmission control unit (345) for controlling the customized warning broadcast signal according to an event situation of a specific object tracked by the smart object tracking control unit to be transmitted to the smart omnidirectional camera device in the field. Smart statistical analysis device using motion trajectory pattern analysis.
A step S100 of photographing a specific object 360 degrees in all directions with a single camera through a smart omnidirectional camera device,
A step S200 of transmitting a donut-type omni-directional image taken by a smart omnidirectional camera device to a remote smart image / statistical analysis server through a data communication interface unit,
Receiving a donut type omni-directional image transmitted from a smart omni-directional camera device in a smart image / statistical analysis server, detecting a specific object by image conversion, and tracking the position of a specific object based on a movement trajectory pattern of the specific object (S300 )Wow,
A step S400 of displaying a statistical analysis report by location and time zone by tracking the position of a specific object on the basis of a moving trajectory pattern of a specific object in the smart image and statistical analysis server and accumulating moving trajectory patterns of a specific object in real time, ,
A step S500 of sending a customized warning broadcast signal according to an event situation of a specific object to a smart omnidirectional camera device in the field,
(S600) of receiving a warning broadcast signal from a warning broadcast control unit of a smart image / statistical analysis server in a smart omnidirectional camera device and transmitting a warning broadcast according to an event condition of a specific object Smart statistical analysis device using motion trajectory pattern analysis.
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101881524B1 (en) * 2018-04-23 2018-07-24 박영기 The apparatus and method of video surveillance system using intelligent based location information and action cognitive information in subject for video
KR101884611B1 (en) * 2017-02-23 2018-08-02 이노뎁 주식회사 Method of extracting objects-of-Interest out of CCTV video using metadate filtering of moving objects
KR101939096B1 (en) 2018-06-07 2019-01-16 쿠도커뮤니케이션 주식회사 Apparatus for Providing Trajectory and Driving Method Thereof
KR101956008B1 (en) 2018-06-07 2019-03-08 쿠도커뮤니케이션 주식회사 Apparatus for Providing Trajectory and Data Building Method Thereof
KR20190060161A (en) * 2017-11-24 2019-06-03 주식회사 리얼타임테크 Apparatus for analyzing Multi-Distributed Video Data

Families Citing this family (1)

* Cited by examiner, † Cited by third party
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US10769906B2 (en) 2017-08-31 2020-09-08 Hanwha Techwin Co., Ltd. Doorbell, security system including doorbell apparatus, and method of operating the same

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101360246B1 (en) 2013-08-12 2014-02-11 김규미 The multi-functional anti-crime camera system

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101442669B1 (en) * 2013-03-22 2014-09-24 에프엔엔(주) Method and apparatus for criminal acts distinction using intelligent object sensing
KR101377029B1 (en) * 2013-11-29 2014-03-20 주식회사 에보시스 The apparatus and method of monitoring cctv with control moudule

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101360246B1 (en) 2013-08-12 2014-02-11 김규미 The multi-functional anti-crime camera system

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US10271018B2 (en) 2017-02-23 2019-04-23 Innodep Co., Ltd. Method of detecting critical objects from CCTV video using metadata filtering
KR20190060161A (en) * 2017-11-24 2019-06-03 주식회사 리얼타임테크 Apparatus for analyzing Multi-Distributed Video Data
KR101881524B1 (en) * 2018-04-23 2018-07-24 박영기 The apparatus and method of video surveillance system using intelligent based location information and action cognitive information in subject for video
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KR101956008B1 (en) 2018-06-07 2019-03-08 쿠도커뮤니케이션 주식회사 Apparatus for Providing Trajectory and Data Building Method Thereof

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