JP2012109733A - Monitoring system and monitoring apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a monitoring system that can automatically track and image an intruder into a monitored area, and even when a plurality of intruders intrude simultaneously, can image all the plurality of intruders.SOLUTION: A monitoring system 5 includes a monitoring apparatus 3 and a display device 6. The monitoring apparatus 3 has: wide angle cameras 11A, 11B for imaging a predetermined monitored area 4; a telephoto camera 12A for, when a moving object is included in pickup images captured by the wide angle cameras 11A, 11B, automatically tracking and imaging the moving object to acquire an enlarged image 300 of the moving object and display it on the display device 6; and a telephoto camera 12B capable of being remote-controlled by an operator to acquire an image of a desired region in the monitored area 4 and display it on the display device 6 independently of the wide angle cameras 11A, 11B and the telephoto camera 12A.

Description

  The present invention relates to a monitoring system and a monitoring device, and more particularly to a monitoring system and a monitoring device for monitoring an intruder into a predetermined monitoring area.

  2. Description of the Related Art A monitoring device that monitors an intruder into a monitoring area by photographing a predetermined monitoring area with a monitoring camera has been widely put into practical use. In such a monitoring apparatus, generally, an intruder into the monitoring area is monitored by displaying a video of the monitoring area captured by the monitoring camera on the monitor and viewing the displayed video by the monitoring person. .

  Patent Document 1 listed below discloses a surveillance camera equipped with a pan / tilt function and a zoom function. When the surveillance camera detects a moving object, the surveillance camera adjusts the angle of view of the zoom lens based on the size and motion vector of the moving object, and also adjusts the shooting range by the pantilter.

Japanese Patent No. 4293236

  However, in the monitoring of an intruder when the monitor visually observes the display image on the monitor, the monitor does not always watch the monitor, so the monitor may miss the intruder. In particular, when a plurality of surveillance cameras are installed around the facility and the images of the plurality of surveillance cameras are monitored by a single supervisor, the possibility that the supervisor overlooks the intruder increases.

  In addition, according to the surveillance camera disclosed in Patent Document 1, it is possible to automatically track an intruder by pan / tilt control and zoom control, but when a plurality of intruders enter the surveillance area at the same time. Therefore, it is impossible to capture all of the intruders without omission. For example, when two intruders intrude into the surveillance area at the same time, when the automatic tracking photographing of one intruder is started by the surveillance camera, the other intruder is not photographed. Therefore, the function of the surveillance camera is insufficient.

  The present invention has been made in view of such circumstances, and it is possible to automatically track an intruder into a surveillance area and photograph it, and even when a plurality of intruders invades at the same time, the plurality of intrusions It is an object of the present invention to obtain a monitoring system and a monitoring apparatus capable of photographing a person without omission.

  A monitoring system according to a first aspect of the present invention includes a monitoring device and a display device, and the monitoring device images a first monitoring area and the first imaging unit. When a moving object is included in the captured image captured by the above, a magnified image of the moving object is acquired and displayed on the display device by automatically tracking and capturing the moving object. By remotely operating the image capturing unit and an operator, an image of a desired location in the monitoring area is acquired independently of the first image capturing unit and the second image capturing unit, and the image is displayed on the display device. And a third photographing means capable of displaying.

  According to the monitoring system of the first aspect, the second imaging unit automatically tracks the moving object when the moving image is captured in the captured image captured by the first imaging unit. By photographing, an enlarged image of the moving object is acquired and displayed on the display device. As described above, the intruder into the monitoring area is automatically tracked and photographed by the second photographing means, so that an enlarged image of the intruder can be photographed without omission. Further, the third imaging unit is remotely operated by an operator to acquire and display an image of a desired location in the monitoring area independently of the first imaging unit and the second imaging unit. Display on the device. Therefore, even when a plurality of intruders enter the monitoring area at the same time, an intruder different from the intruder that is photographed by the second photographing means can be photographed by the third photographing means. As a result, a plurality of intruders can be photographed without omission.

  The monitoring system according to the second aspect of the present invention is the monitoring system according to the first aspect, in particular, the third imaging means is for imaging a desired location by remote operation of an operator and imaging a moving object by automatic tracking. And can be switched.

  According to the monitoring system of the second aspect, the third imaging unit can switch between imaging of a desired location by remote operation of the operator and imaging of a moving object by automatic tracking. Therefore, when a plurality of intruders intrude into the monitoring area at the same time, an operation of automatically tracking and photographing a plurality of intruders using the second and third photographing means, and an intruder by the second photographing means. Since the third image capturing unit can be switched to the operation of capturing another desired intruder while automatically tracking and capturing the image, the convenience of the user can be improved.

  The monitoring system according to the third aspect of the present invention is the monitoring system according to the first or second aspect, in particular, the position in the monitoring area being imaged by the second imaging means, and the third Position information indicating the position in the monitoring area being photographed by the photographing means and the position of the moving object in the monitoring area is further displayed on the display device.

  According to the monitoring system according to the third aspect, the position in the monitoring area photographed by the second photographing means, the position in the monitoring area photographed by the third photographing means, and in the monitoring area Position information indicating the position of the moving object is displayed on the display device. Therefore, the operator can easily identify the intruder to be photographed next by the third photographing means based on the position information, and thus can photograph a plurality of intruders without omission.

  The monitoring system according to a fourth aspect of the present invention is the monitoring system according to any one of the first to third aspects, and particularly includes a moving object in a photographed image photographed by the first photographing means. In the case of an image region corresponding to the moving object in the captured image, a spectrum of specific wavelengths including an infrared region is detected, and the material of the moving object is analyzed based on the detection result. Material analysis means; and data generation means for generating feature data representing the feature amount of the moving object including parameters relating to the material of the moving object, and automatically tracking the moving object based on the feature data Is performed.

  According to the monitoring system according to the fourth aspect, the material analysis means detects the spectrum of a plurality of specific wavelengths including the infrared region with respect to the image region corresponding to the moving object in the captured image, and uses the result of the detection as a result. Based on this, the material of the moving object is analyzed. Therefore, when human skin, chemical fiber, or the like is included in the image area corresponding to the moving object as a result of the material analysis, the moving object can be identified as a human. As a result, when a moving object is included in a predetermined monitoring area, it is possible to accurately identify whether the moving object is a human being or an animal other than that. In addition, the data generation unit generates feature data representing the feature amount of the moving object, including parameters related to the material of the moving object analyzed by the material analysis unit. Then, automatic tracking of the moving object is performed based on the feature data. Therefore, it is possible to accurately track individual moving objects that move within the monitoring area based on the feature data regarding each moving object.

  The monitoring system according to a fifth aspect of the present invention is the monitoring system according to the fourth aspect, in particular, a plurality of the monitoring areas are photographed by a plurality of the monitoring devices, and different monitoring areas are selected based on the feature data. The moving object straddling is automatically tracked.

  According to the monitoring system according to the fifth aspect, based on the feature data regarding each moving object, automatic tracking of the moving object across different monitoring areas can be performed accurately.

  The monitoring apparatus according to the sixth aspect of the present invention includes a first imaging unit that images a predetermined monitoring area, and a moving object included in the captured image captured by the first imaging unit. In addition, the moving object is automatically tracked and photographed to acquire an enlarged image of the moving object, and the first photographing means and the first photographing means are remotely operated by an operator. Independently of the second photographing means, a third photographing means for obtaining an image of a desired location in the monitoring area is provided.

  According to the monitoring apparatus of the sixth aspect, the second imaging unit automatically tracks the moving object when the moving image is captured by the first imaging unit. An enlarged image of the moving object is acquired by photographing. As described above, the intruder into the monitoring area is automatically tracked and photographed by the second photographing means, so that an enlarged image of the intruder can be photographed without omission. In addition, the third imaging unit is remotely operated by an operator, and acquires an image of a desired location in the monitoring area independently of the first imaging unit and the second imaging unit. Therefore, even when a plurality of intruders enter the monitoring area at the same time, an intruder different from the intruder that is photographed by the second photographing means can be photographed by the third photographing means. As a result, a plurality of intruders can be photographed without omission.

  According to the present invention, intruders can be automatically tracked and photographed, and even when a plurality of intruders enter at the same time, the plurality of intruders can be photographed without omission. A monitoring system and a monitoring device can be obtained.

It is a figure which shows an example of the usage condition of the monitoring apparatus which concerns on embodiment of this invention. It is a figure showing roughly the whole surveillance system composition concerning an embodiment of the invention. It is a figure which shows typically the external appearance of a monitoring apparatus. It is a block diagram which shows the function of a monitoring apparatus roughly. FIG. 5 is a diagram specifically illustrating a configuration of each unit illustrated in FIG. 4. It is a figure which shows the 1st example of a structure of a light receiving element part. It is a figure which shows the 2nd example of a structure of a light receiving element part. It is a figure which shows the 1st example of a structure of a wavelength selection filter and a light receiving element part. It is a figure which shows the 2nd example of a structure of a wavelength selection filter and a light receiving element part. It is a block diagram which shows the structure of a material analysis part. It is a flowchart which shows the whole operation | movement of a monitoring apparatus. It is a figure which shows the picked-up image each image | photographed with the wide angle camera. It is a flowchart which shows the identification process of the material by a material identification part. It is a flowchart which shows the identification process of the material by a material identification part. It is a figure which shows the enlarged image which image | photographed the intruder with the telephoto camera. It is a figure which shows an example of the position information map produced by the position specific | specification part. It is a figure which shows an example of the image displayed on a display apparatus. It is a figure which shows the other example of the image displayed on a display apparatus. It is a figure which shows the condition where the some monitoring apparatus was installed in the communication base station.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In addition, the element which attached | subjected the same code | symbol in different drawing shall show the same or corresponding element.

  FIG. 1 is a diagram illustrating an example of a usage state of the monitoring device 3 according to the embodiment of the present invention. A communication base station 1 is installed in the mountains, and the communication base station 1 is surrounded by a fence 2. In this example, the monitoring device 3 is used for the purpose of monitoring an intruder trying to get over the fence 2 and enter the communication base station 1 by shooting the monitoring area 4 including the fence 2 as a predetermined shooting area. Is done. In the example of FIG. 1, only one monitoring device 3 is installed in the communication base station 1. However, as shown in FIG. 19 described later, in order to monitor the periphery of the communication base station 1 without blind spots, Monitoring devices 3A to 3D may be installed.

  FIG. 2 is a diagram schematically showing the overall configuration of the monitoring system 5 according to the embodiment of the present invention. The monitoring system 5 includes a monitoring device 3 and a display device 6 such as a liquid crystal display that displays an image captured by the monitoring device 3. The display device 6 is installed in a remote monitoring center (or in the communication base station 1), and an image displayed on the display device 6 is visible by an operator (monitoring person). An operation unit 7 that can be operated by an operator to remotely operate the monitoring device 3 is installed in the monitoring center.

  FIG. 3 is a diagram schematically illustrating the appearance of the monitoring device 3. A pair of wide-angle cameras 11A and 11B that function as stereo cameras, telephoto cameras 12A and 12B, and a control device 13 are attached to the frame 10. The wide-angle cameras 11A and 11B have a fixed field of view so that the entire monitoring area 4 can be photographed. The telephoto cameras 12A and 12B are, for example, PTZ cameras equipped with a pan / tilt function and a zoom function. The wide-angle cameras 11A and 11B and the telephoto cameras 12A and 12B capture the object by receiving reflected sunlight from the object. However, the monitoring device 3 may be provided with a light irradiator for irradiating the monitoring area 4 with halogen light or infrared light so as to enable photographing at night.

  FIG. 4 is a block diagram schematically showing the function of the monitoring device 3. The monitoring device 3 includes an imaging unit 21, an analysis unit 22, an identification unit 23, a feature data generation unit 24, and a data processing unit 40. The photographing unit 21 includes the wide-angle cameras 11A and 11B and the telephoto cameras 12A and 12B shown in FIG. FIG. 5 is a diagram specifically illustrating the configuration of each unit illustrated in FIG. 4.

  4 and 5, the photographing unit 21 includes an optical system 31A corresponding to the wide-angle camera 11A, a branching unit 32A, a light receiving element unit 33A, a wavelength selection filter 34A, and a light receiving element unit 35A. And an optical system 31B corresponding to the wide-angle camera 11B, a branching section 32B, a light receiving element section 33B, a wavelength selection filter 34B, and a light receiving element section 35B. In the following description, the wide-angle cameras 11A and 11B are collectively referred to as “wide-angle camera 11”, the optical systems 31A and 31B are collectively referred to as “optical system 31”, and the branch portions 32A and 32B are collectively referred to. The light receiving element portions 33A and 33B are collectively referred to as “light receiving element portion 33”, the wavelength selection filters 34A and 34B are collectively referred to as “wavelength selection filter 34”, and the light receiving element portion 35A. , 35B are collectively referred to as “light receiving element portion 35”.

  The analysis unit 22 includes a moving object detection unit 36A, an extraction unit 37A, a shape analysis unit 38A, and a material analysis unit 39A corresponding to the wide-angle camera 11A, and a moving object detection unit 36B, an extraction unit 37B, and a shape analysis unit corresponding to the wide-angle camera 11B. 38B and a material analysis unit 39B.

  The identification unit 23 includes an identification unit 23A corresponding to the wide-angle camera 11A and an identification unit 23B corresponding to the wide-angle camera 11B.

  The feature data generation unit 24 includes a feature data generation unit 24A corresponding to the wide-angle camera 11A and a feature data generation unit 24B corresponding to the wide-angle camera 11B.

  The data processing unit 40 includes an identical target specifying unit 41, an individual target specifying unit 42, a position specifying unit 43, and a tracking processing unit 44.

  FIG. 6 is a diagram illustrating a first example of the configuration of the light receiving element portions 33 and 35. FIG. 6A shows the configuration of the light receiving element portion 33, and FIG. 6B shows the configuration of the light receiving element portion 35. The light receiving element section 33 has a configuration in which a plurality of light receiving elements such as CCDs are arranged in a matrix. The light receiving element portion 35 has a configuration in which a plurality of light receiving elements using InGaAs or the like are arranged in a matrix. In the example of FIG. 6, the number of pixels of the light receiving element portion 33 and the number of pixels of the light receiving element portion 35 are equal to each other, and each pixel of the light receiving element portions 33 and 35 corresponds to one to one. That is, the spatial resolutions of the light receiving element portions 33 and 35 are equal to each other.

  FIG. 7 is a diagram illustrating a second example of the configuration of the light receiving element portions 33 and 35. As in FIG. 6, FIG. 7A shows the configuration of the light receiving element portion 33, and FIG. 7B shows the configuration of the light receiving element portion 35. In the example of FIG. 7, the number of pixels of the light receiving element unit 35 is set to be smaller than the number of pixels of the light receiving element unit 33 in order to reduce the processing load in the material analyzing units 39A and 39B described later. That is, the spatial resolution of the light receiving element unit 35 is lower than the spatial resolution of the light receiving element unit 33.

  With reference to FIG. 5, the reflected light from the object is guided onto the light receiving element portion 33 by the optical system 31. Each light receiving element constituting the light receiving element unit 33 outputs an electrical signal having a magnitude corresponding to the received light intensity of the reflected light in the visible light wavelength range. Further, an image taken by the wide-angle camera 11 is displayed on the display device 6 shown in FIG.

  The branching unit 32 is a prism or a half mirror, and is arranged between the optical system 31 and the light receiving element unit 33. The reflected light traveling from the optical system 31 toward the light receiving element unit 33 is branched toward the light receiving element unit 35 by the branching unit 32. The branched reflected light is guided onto the light receiving element portion 35 through the wavelength selection filter 34. Each light receiving element constituting the light receiving element unit 35 outputs an electrical signal having a magnitude corresponding to the received light intensity of the reflected light in the wavelength range of infrared light.

  In addition, as a structure of the branch part 32, it is good also as a structure which arrange | positions the reflective mirror which can be inserted or retracted between the optical system 31 and the light receiving element part 33 instead of the structure which uses a fixed prism or a half mirror. At the first timing, the reflecting mirror is retracted from the optical path between the optical system 31 and the light receiving element unit 33. Thereby, the reflected light from the object is guided onto the light receiving element portion 33. Further, at the second timing, the reflecting mirror is inserted on the optical path between the optical system 31 and the light receiving element portion 33. The reflected light from the optical system 31 toward the light receiving element portion 33 is reflected toward the light receiving element portion 35 by the reflecting mirror. Thereby, the reflected light from the object is guided onto the light receiving element portion 35. The first and second timings are alternately repeated at predetermined minute time intervals.

  FIG. 8 is a diagram illustrating a first example of the configuration of the wavelength selection filter 34 and the light receiving element unit 35. The wavelength selection filter 34 includes five wavelength selection filters 51 to 55 each having a size substantially equal to the light receiving surface of the light receiving element portion 35. The wavelength selection filters 51, 52, 53, 54, and 55 transmit only the wavelength components of the 1100 nm band, the 1200 nm band, the 1300 nm band, the 1500 nm band, and the 1600 nm band, respectively, of the reflected light incident from the branching unit 32. The wavelength selection filters 51 to 55 are sequentially inserted in front of the light receiving surface of the light receiving element unit 35. Thereby, the light receiving element part 35 receives the reflected light of the wavelength component corresponding to each wavelength selection filter 51-55 in order.

  FIG. 9 is a diagram illustrating a second example of the configuration of the wavelength selection filter 34 and the light receiving element unit 35. The light receiving element unit 35 has a configuration in which light receiving element units 351 to 355 having the same structure are arranged in parallel. A wavelength selective filter is provided in front of each light receiving surface of the light receiving element units 351, 352, 353, 354, and 355. 51, 52, 53, 54, 55 are arranged, respectively. The reflected light branched by the branch part 32 is further branched toward the light receiving element parts 351 to 355 by an additional branch part (not shown). Thereby, the light receiving element part 35 receives the reflected light of the wavelength component corresponding to each wavelength selection filter 51-55 in parallel.

  FIG. 10 is a block diagram showing the configuration of the material analysis unit 39A. The material analysis unit 39A includes a reflectance calculation unit 91A, a normalization index calculation unit 92A, a secondary differential value calculation unit 93A, and a material identification unit 94A. The material analysis unit 39A includes a 1100 nm band, a 1200 nm band, a 1300 nm band, a 1500 nm band, and a 1600 nm band with respect to an image region corresponding to a moving object included in the captured image of the captured image captured by the wide-angle camera 11A. The spectrum of each wavelength component of the band is detected. Then, the material of the moving object is identified based on the detection result of the spectrum. 10 shows the configuration of the material analysis unit 39A, the configuration of the material analysis unit 39B is the same as this.

  FIG. 11 is a flowchart showing the overall operation of the monitoring device 3. Hereinafter, the operation of the monitoring device 3 will be described in detail according to the flowchart shown in FIG.

  In step P11, the entire monitoring area 4 is always photographed by the wide-angle cameras 11A and 11B.

  FIG. 12 is a diagram illustrating captured images 200A and 200B captured by the wide-angle cameras 11A and 11B, respectively. FIG. 12A shows a situation in which intruders 61 to 63 have entered the monitoring area 4, and FIG. 12B shows the situation in FIG. 12A by the wide-angle camera 11A. A photographed image 200A is shown, and FIG. 12C shows a photographed image 200B obtained by photographing the situation of FIG. 12A with the wide-angle camera 11B. Since the wide-angle cameras 11A and 11B capture the monitoring area 4 from different directions, the positions of the intruders 61 to 63 in the captured images 200A and 200B are different from each other due to the parallax.

  Referring to the flowchart of FIG. 11, next, in step P <b> 12, it is determined whether or not any moving object is included in the monitoring area 4. Specifically, referring to FIG. 5, captured images 200A and 200B captured by wide-angle cameras 11A and 11B are input from light receiving element units 33A and 33B to moving object detection units 36A and 36B, respectively. Then, the moving object detection units 36A and 36B respectively determine whether or not a moving object is included in the captured images 200A and 200B based on the difference between the continuous images sequentially input in time series. In addition, when a moving object is included, the moving object detection units 36A and 36B each specify an image area corresponding to the moving object from the entire areas of the captured images 200A and 200B. In the example of FIG. 12, the moving object detection unit 36A specifies the image areas 71 to 73, and the moving object detection unit 36B specifies the image areas 74 to 76.

  Referring to the flowchart of FIG. 11, when a moving object is not included in monitoring area 4 (that is, when the determination result in step P12 is “NO”), the operations of steps P11 and P12 are repeatedly executed. On the other hand, when a moving object is included in the monitoring area 4 (that is, when the determination result in Step P12 is “YES”), shape analysis and spectrum analysis of the moving object are performed in Step P13. Specifically, referring to FIG. 5, the extraction unit 37A extracts the image regions 71 to 73 specified by the moving object detection unit 36A from the captured image 200A in the visible range, and shapes the extracted image regions 71 to 73 into shapes. The data is input to the analysis unit 38A. The extraction unit 37A extracts the image regions 71 to 73 specified by the moving object detection unit 36A from the infrared captured image 200A, and inputs the extracted image regions 71 to 73 to the material analysis unit 39A.

  The shape analysis unit 38A performs pattern matching on each of the image regions 71 and 72 using a plurality of template images (prepared in advance and stored in a storage unit (not shown)) related to the appearance of the person, thereby Each of the moving objects included in 71 to 73 is analyzed as to whether or not it is a human. The shape analysis unit 38A inputs parameter information indicating the accuracy that the moving object included in each of the image regions 71 to 73 is a human to the identification unit 23A at the subsequent stage.

  The material analysis unit 39A detects the spectrum of the wavelength components of the 1100 nm band, the 1200 nm band, the 1300 nm band, the 1500 nm band, and the 1600 nm band for each of the image areas 71 to 73, and based on the detection result, the image areas 71 to 73 are detected. The material of the moving object included in 73 is analyzed.

  Hereinafter, the contents of processing in the material analysis unit 39A will be described in detail. As described above, each light receiving element constituting the light receiving element portion 35A outputs an electric signal having a magnitude corresponding to the received light intensity of the reflected light. The material analysis unit 39A receives electrical signals output from the light receiving elements belonging to the image regions 71 to 73 for the respective wavelength components in the 1100 nm band, 1200 nm band, 1300 nm band, 1500 nm band, and 1600 nm band from the light receiving element unit 35A. It is input via the extraction unit 37A. Referring to FIG. 10, the electric signal is input to reflectance calculation unit 91A.

  Based on the electrical signal input from the light receiving element unit 35A, the reflectance calculation unit 91A reflects the reflectances R1100, R1200, R1300, and R1500 for each wavelength component in the 1100 nm band, 1200 nm band, 1300 nm band, 1500 nm band, and 1600 nm band. , R1600.

Based on the reflectances R1100, R1200, R1300, R1500, and R1600 calculated by the reflectance calculation unit 91A, the normalization index calculation unit 92A calculates normalization indexes ND1 to ND4 defined by the following expressions.
ND1: (R1500-R1300) / (R1500 + R1300)
ND2: (R1500-R1200) / (R1500 + R1200)
ND3: (R1600-R1300) / (R1600 + R1300)
ND4: (R1300-R1100) / (R1300 + R1100)

Further, the secondary differential value calculation unit 93A calculates a secondary differential value of the function of the reflectance and the wavelength. In the present embodiment, the secondary differential value calculation unit 93A is an approximate one defined by the following formula based on the reflectances R1100, R1200, R1300, R1500, and R1600 calculated by the reflectance calculation unit 91A. Second derivative values 2 ^nd der1 and ^nd der2 are calculated.
2 ^nd der1:
[{(R1500-R1300) / (R1500 + R1300)} / 200]
-[{(R1300-R1200) / (R1300 + R1200)} / 100]
2 ^nd der2:
[{(R1500-R1200) / (R1500 + R1200)} / 300]
-[{(R1200-R1100) / (R1200 + R1100)} / 100]

The reflectances R1100, R1200, R1300, R1500, R1600, the normalization indices ND1 to ND4, and the second derivative values 2 ^nd der1 and ^nd der2 are input to the material identification unit 94A.

  The material identifying unit 94A identifies the material of the object (that is, the moving object included in the monitoring area 4) based on the input information.

  13 and 14 are flowcharts showing a material identification process by the material identification unit 94A. First, in step P21, the material identifying unit 94A determines whether or not the values of the reflectances R1100, R1200, R1300, R1500, and R1600 are approximately zero. For example, when the reflectance value is less than a predetermined value (for example, 0.02), the reflectance is determined to be approximately 0, and when the reflectance value is greater than or equal to the predetermined value, It is determined that the reflectance is not approximately 0. When the values of all the reflectances R1100, R1200, R1300, R1500, and R1600 are approximately 0 (that is, when the determination result in Step P21 is “YES”), the material identification unit 94A determines the analysis target range. It is determined that there is a window glass inside (in each image area 71 to 73 in this example).

On the other hand, if the value of any of the reflectances R1100, R1200, R1300, R1500, R1600 is not approximately 0 (that is, if the determination result in step P21 is “NO”), then material identification is performed in step P22. The unit 94A determines whether or not a value “2 ^nd der1 × (ND1 + ND3)” obtained by multiplying the secondary differential value 2 ^nd der1 by the sum of the normalization indices ND1 and ND3 is less than a predetermined threshold Th11.

If the value of “2 ^nd der1 × (ND1 + ND3)” is equal to or greater than the threshold value Th11 (that is, if the determination result in step P22 is “NO”), then in step P23, the material identification unit 94A causes the normalization index It is determined whether or not the value of ND2 is greater than a predetermined threshold value Th12.

  When the value of the normalization index ND2 is larger than the threshold value Th12 (that is, when the determination result in Step P23 is “YES”), the material identifying unit 94A determines that an animal or fabric exists within the analysis target range.

On the other hand, when the value of the normalization index ND2 is equal to or smaller than the threshold Th12 (that is, when the determination result in Step P23 is “NO”), in Step P24, the material identification unit 94A then determines the secondary differential value 2 ^nd. It is determined whether the value of der2 is less than a predetermined threshold Th13.

When the value of the secondary differential value 2 ^nd der2 is less than the threshold Th13 (that is, when the determination result in Step P24 is “YES”), the material identification unit 94A determines that the plant exists in the analysis target range. To do.

On the other hand, when the value of the secondary differential value 2 ^nd der2 is equal to or greater than the threshold Th13 (that is, when the determination result in Step P24 is “NO”), the material identification unit 94A determines that the human skin is within the analysis target range. It is determined that it exists.

If the value of “2 ^nd der1 × (ND1 + ND3)” is greater than or equal to the threshold Th11 in the determination in Step P22 (that is, if the determination result in Step P22 is “NO”), then material identification is performed in Step P25. The unit 94A determines whether or not the value of the normalization index ND3 is less than a predetermined threshold Th14.

  If the value of the normalized index ND3 is less than the threshold Th14 (that is, if the determination result in Step P25 is “YES”), then in Step P26, the material identifying unit 94A determines that the value of the normalized index ND4 is a predetermined value. It is determined whether it is less than the threshold value Th15.

  When the value of the normalization index ND4 is less than the threshold Th15 (that is, when the determination result in Step P26 is “YES”), the material identification unit 94A determines that the metal exists within the analysis target range.

  On the other hand, when the value of the normalization index ND4 is equal to or greater than the threshold Th15 (that is, when the determination result in Step P26 is “NO”), the material identification unit 94A determines that concrete or stone exists within the analysis target range. judge.

  If the value of the normalization index ND3 is greater than or equal to the threshold Th14 in the determination in step P25 (that is, if the determination result in step P25 is “NO”), then in step P27, the material identification unit 94A It is determined whether the value of the optimization index ND2 is less than a predetermined threshold Th16.

  When the value of the normalization index ND2 is less than the threshold Th16 (that is, when the determination result in Step P27 is “YES”), the material identification unit 94A determines that asphalt exists within the analysis target range.

  On the other hand, when the value of the normalization index ND2 is equal to or greater than the threshold Th16 (that is, when the determination result in Step P27 is “NO”), the material identification unit 94A determines that concrete or stone exists within the analysis target range. judge.

  In addition, each threshold value Th11 to Th16 is appropriately set so that a target can be accurately identified by setting a measurement region in advance for a known target such as metal or human skin and performing the above identification flow by the material identifying unit 94A. Set to the correct value.

  As a result, when the material identifying unit 94A determines that human skin exists within the analysis target range, the material identifying unit 94A identifies that the type of the moving object included in the monitoring area 4 is human. On the other hand, in other cases, the type of the moving object included in the monitoring area 4 is identified as not being human. For example, when it is determined that a window glass or metal exists within the analysis target range, the type of the moving object included in the monitoring area 4 is identified as a car.

  In addition, the situation where the intruder into the monitoring area 4 does not expose human skin by wearing a cover or gloves is also assumed. Therefore, if it is determined that a chemical fiber is present in the analysis target range by setting an identification flow that can detect a material such as a chemical fiber worn only by humans, the movement included in the monitoring area 4 The object type may be identified as human. In addition, by setting an identification flow that can detect the type of fiber such as wool, cotton, nylon, and polyester, it is possible to identify the material of clothes worn by humans.

  Referring to FIG. 5, the material analysis unit 39A inputs parameter information indicating the accuracy that the moving object included in each of the image regions 71 to 73 is a human to the identification unit 23A at the subsequent stage.

  In the above description, the processing in the shape analysis unit 38A and the material analysis unit 39A corresponding to the wide-angle camera 11A has been described, but the processing in the shape analysis unit 38B and the material analysis unit 39B corresponding to the wide-angle camera 11B is similar to this. Therefore, redundant description is omitted.

  Referring to the flowchart of FIG. 11, next in step P14, the identification unit 23A determines that the moving objects included in the image regions 71 to 73 input from the shape analysis unit 38A and the material analysis unit 39A are human. Based on the parameter information indicating the certainty of being, it is determined whether or not the moving object included in each of the image areas 71 to 73 is a human. For example, when both values of the parameter information input from the shape analysis unit 38A and the material analysis unit 39A are equal to or greater than a predetermined threshold, the moving object included in each of the image regions 71 to 73 is identified as a human being. To do.

  Here, when the size of each of the image regions 71 to 73 in the captured image 200A is small (particularly when the spatial resolution of the light receiving element unit 35 is low as shown in FIG. 7), the material analysis by the material analysis unit 39A. Accuracy may be reduced. Therefore, when the size of each of the image areas 71 to 73 in the captured image 200A is smaller than the predetermined value, the identification unit 23A uses the parameter input from the shape analysis unit 38A rather than the parameter information input from the material analysis unit 39A. Emphasizing information, it is determined whether or not the moving object included in each of the image areas 71 to 73 is a human. For example, when the size of each of the image areas 71 to 73 is less than the predetermined value, identification is performed based only on the parameter information input from the shape analysis unit 38A, and the size of each of the image areas 71 and 72 is the predetermined value. If the value is greater than or equal to the value, identification is performed based on parameter information input from both the shape analysis unit 38A and the material analysis unit 39A.

  In the above description, the process in the identification unit 23A corresponding to the wide-angle camera 11A has been described, but the process in the identification unit 23B corresponding to the wide-angle camera 11B is the same as this.

  When the moving object included in each of the image areas 71 to 73 is identified as not being human (that is, when the determination result in Step P14 is “NO”), the operations after Step P11 are repeatedly executed. On the other hand, when the moving object included in each of the image areas 71 to 73 is identified as a human (that is, an intruder) (that is, when the determination result in Step P14 is “YES”), the next step P15 is performed. The feature data generation unit 24A generates feature data representing the feature amount of the moving object included in each of the image regions 71 to 73. For example, for each moving object, the position coordinates in the row direction and the column direction in the photographed image 200A, the amount of change in position from the previous frame, the material information obtained for each pixel by the material analysis unit 39A, and the like are described as parameters. Generate feature data. By describing the material information for each pixel, information on the material of the clothes worn by the intruder can be included in the feature data. The feature data regarding each moving object generated by the feature data generation unit 24A is input to the data processing unit 40.

  In the above description, the process in the feature data generation unit 24A corresponding to the wide-angle camera 11A has been described, but the process in the feature data generation unit 24B corresponding to the wide-angle camera 11B is the same as this. The feature data related to the moving object included in the image regions 74 to 76 generated by the feature data generation unit 24A is input from the feature data generation unit 24B to the data processing unit 40.

  Referring to the flowchart of FIG. 11, next in step P16, the individual object specifying unit 42 is included in each of the captured images 200A and 200B based on the feature data input from the feature data generating units 24A and 24B, respectively. Identify moving objects individually. For example, when the intruder 61 is wearing a covering surface and the intruders 62 and 63 are not wearing a covering surface, the material of the face portion of the intruder 61 is a fiber, while the face of the intruder 62 or 63 is The material of the part is human skin. Therefore, the individual target specifying unit 42 can distinguish between the intruder 61 and the intruders 62 and 63 based on the difference in the material of the face portion. Moreover, when the materials of the clothes worn by the intruder 62 and the intruder 63 are different, the materials of the body parts of the intruders 62 and 63 are different from each other. Therefore, the individual object specifying unit 42 can distinguish the intruders 62 and 63 individually based on the difference in the material of the body part. In the present embodiment, the individual target specifying unit 42 specifies the intruder 61 based on the feature data corresponding to the image region 71, specifies the intruder 62 based on the feature data corresponding to the image region 72, and The intruder 63 is specified based on the feature data corresponding to the area 73. Similarly, the individual target specifying unit 42 specifies the intruder 61 based on the feature data corresponding to the image area 74, specifies the intruder 62 based on the feature data corresponding to the image area 75, and sets the image area 76. The intruder 63 is specified based on the corresponding feature data.

  In step P16, the same target specifying unit 41 specifies the same target moving object included in the captured images 200A and 200B based on the feature data respectively input from the feature data generating units 24A and 24B. In the present embodiment, the same target specifying unit 41 is the same target (intruder 61) for a human included in the image area 71 of the captured image 200A and a human included in the image area 74 of the captured image 200B. The person included in the image area 72 of the photographed image 200A and the person included in the image area 75 of the photographed image 200B are identified as the same target (intruder 62), and photographed. The person included in the image area 73 of the image 200A and the person included in the image area 76 of the captured image 200B are specified as the same target (intruder 63).

  Next, in step P17, the position specifying unit 43 enters the surveillance area 4 based on the distance between the wide-angle cameras 11A and 11B and the positional relationship between the image areas 71 and 74 of the same target in the captured images 200A and 200B. The position of the person 61 is specified. Similarly, the position specifying unit 43 is based on the distance between the wide-angle cameras 11A and 11B and the positional relationship between the image areas 72 and 75 of the same target in the captured images 200A and 200B. Specify the position of. Similarly, the position specifying unit 43 is based on the distance between the wide-angle cameras 11A and 11B and the positional relationship between the image areas 73 and 76 of the same target in the captured images 200A and 200B. Specify the position of.

  In step P <b> 17, the position specifying unit 43 creates a position information map indicating the positions of the intruders 61 to 63 in the monitoring area 4. FIG. 16 is a diagram illustrating an example of the position information map 250 created by the position specifying unit 43. Figures 81, 82, 83 showing the positions of the intruders 61, 62, 63 in the monitoring area 4 are displayed on the plane map corresponding to the monitoring area 4. In the position information map 250, an area that requires particularly important monitoring in the monitoring area 4 (for example, an area close to the entrance to the building of the communication base station 1) is set as the priority monitoring area 80. The priority monitoring area 80 can be arbitrarily set in advance in the monitoring area 4. In the example of FIG. 16, the figure 81 corresponding to the intruder 61 is included in the priority monitoring area 80, and the figures 82 and 83 corresponding to the intruders 62 and 63 are included outside the priority monitoring area 80. .

  In this embodiment, it is assumed that the monitoring device 3 is used for monitoring an intruder who tries to enter the communication base station 1 over the fence 2, and the height direction when the fence 2 is exceeded It is also necessary to consider the amount of movement. Since the stereo camera is configured by using the two wide-angle cameras 11A and 11B, the position of the intruder including the height direction and the distance to the intruder can be specified. However, it is not always necessary to use a stereo camera, and only one wide-angle camera may be used.

  Next, in step P18, photographing with the telephoto camera 12A is performed with the position of the moving object identified by the position identifying unit 43 as the center of the visual field. The telephoto camera 12 </ b> A captures the most important intruder among the intruders 61 to 63 included in the monitoring area 4. In the position information map 250 illustrated in FIG. 16, the importance of the intruder 61 included in the priority monitoring area 80 is higher than the importance of the intruders 62 and 63 included outside the priority monitoring area 80. By setting it high, the intruder 61 is photographed by the telephoto camera 12A. Information indicating the position of the intruder 61 in the monitoring area 4 is notified from the position specifying unit 43 to the telephoto camera 12A, and the telephoto camera 12A captures the notified position. Here, when a plurality of intruders are included in the priority monitoring area 80, the telephoto camera 12A captures the plurality of intruders alternately at a predetermined time interval.

  Note that the importance setting method is not limited to the above example, but is arbitrary. For example, the newer (or older) intruder who entered the monitoring area 4 can set the importance level higher. Alternatively, an intruder with a higher moving speed can set a higher importance level. Alternatively, an intruder with a larger velocity component moving in a direction approaching the entrance / exit of the communication base station 1 can set the importance level higher. Or an intruder with a short distance from the entrance / exit of the communication base station 1 can set a higher importance. Moreover, you may set importance by combining these elements arbitrarily.

  FIG. 15 is a diagram showing an enlarged image 300 obtained by photographing the intruder 61 with the telephoto camera 12A. The enlarged image 300 is recorded on an arbitrary recording medium such as a hard disk or a semiconductor memory, and is displayed on the display device 6 shown in FIG.

  In step P18, the telephoto camera 12B performs imaging using the position of the moving object specified by the position specifying unit 43 as the center of the visual field. The telephoto camera 12B photographs the intruder having the second highest importance among the intruders 61 to 63 included in the monitoring area 4. In the position information map 250 illustrated in FIG. 16, the importance of the intruder 63 near the priority monitoring area 80 among the intruders 62 and 63 is set higher than the importance of the intruder 62, so that the telephoto camera is set. The intruder 63 is photographed by 12B. Information indicating the position of the intruder 63 in the monitoring area 4 is notified from the position specifying unit 43 to the telephoto camera 12B, and the telephoto camera 12B captures the notified position. The telephoto camera 12B may alternately photograph the intruders 62 and 63 at a predetermined time interval. An enlarged image taken by the telephoto camera 12B is recorded on an arbitrary recording medium such as a hard disk or a semiconductor memory, and is displayed on the display device 6 shown in FIG.

  In addition, the monitoring device 3 shoots the intruders 61 to 63 with the telephoto cameras 12A and 12B, and gives a predetermined warning to the intruders 61 to 63 by sound or light.

  When the intruders 61 to 63 move within the monitoring area 4, the positions of the image areas 71 to 73 change in the plurality of captured images 200A arranged in time series. The tracking processing unit 44 tracks position changes of the image regions 71 to 73 accompanying the movement of the intruders 61 to 63 by searching for image regions in which the feature data match or approximate in the continuous captured images 200A. Similarly, the tracking processing unit 44 searches for an image area in which the feature data matches or approximates in the continuous captured image 200B, thereby changing the position of the image areas 74 to 76 accompanying the movement of the intruders 61 to 63. Chase. Thus, the intruders 61 to 63 can be automatically tracked and photographed by the telephoto cameras 12A and 12B.

  FIG. 17 is a diagram illustrating an example of an image displayed on the display device 6. The display screen of the display device 6 is divided into four areas 151, 152, 153 and 154. In the area 151, an entire image of the monitoring area 4 captured by the wide-angle camera 11A is displayed. In the area 152, an enlarged image of the intruder 61 photographed by the telephoto camera 12A is displayed.

  In the area 153, an enlarged image of the intruder 63 captured by the telephoto camera 12B is displayed. In the area 154, the position information map 250 created by the position specifying unit 43 is displayed. In the position display map 250, a graphic 85 indicating the position in the monitoring area 4 currently captured by the telephoto camera 12A and a graphic 86 indicating the position in the monitoring area 4 currently captured by the telephoto camera 12B are shown. Also displayed.

  In the area 153, information indicating that the telephoto camera 12B is in the automatic tracking mode (and information indicating that switching to the manual shooting mode) and selection selected by the operator when switching to the manual shooting mode are performed. A button 88 is also displayed. The display device 6 has a function as a touch panel. When the operator touches the selection button 88, the telephoto camera 12B starts from an automatic shooting mode in which an intruder having the second highest importance is automatically tracked and shot. The manual shooting mode can be switched by the operator's remote operation. In the manual photographing mode, the operator can remotely control the pan / tilt function and the zoom function of the telephoto camera 12B using the operation unit 7 shown in FIG. Can be taken. For example, in a situation where the telephoto camera 12B in the automatic tracking mode is photographing the intruder 63, when the operator wants to photograph the intruder 62 instead of the intruder 63, the operator switches the telephoto camera 12B to the manual photographing mode, The intruder 62 can be photographed by the telephoto camera 12B by specifying the photographing position using the operation unit 7 while referring to the position information map 250 displayed in the area 154.

  FIG. 18 is a diagram illustrating another example of an image displayed on the display device 6. In the area 153, an enlarged image of the intruder 62 captured by the telephoto camera 12B in the manual photographing mode is displayed. In addition, when the shooting mode of the telephoto camera 12B is switched from the automatic tracking mode to the manual shooting mode, information indicating that the telephoto camera 12B is in the manual shooting mode (and the automatic tracking mode can be switched to the area 153). Information indicating that there is) and a selection button 89 selected by the operator when switching to the automatic tracking mode are displayed together.

  Referring to the flowchart of FIG. 11, next, in step P <b> 19, it is determined whether or not the intruders 61 to 63 have left the monitoring area 4. When the intruders 61 to 63 are staying in the monitoring area 4 (that is, when the determination result in Step P19 is “NO”), the operations after Step P16 are repeated. On the other hand, when the intruders 61 to 63 have left the monitoring area 4 (that is, when the determination result in Step P19 is “YES”), the operations after Step P11 are repeated.

  The drive control of the telephoto cameras 12A and 12B for automatic tracking of intruders is performed by the control unit 13 shown in FIG. However, by installing a Field Programmable Gate Array (FPGA) and a DSP (Digital Signal Processor) storing a predetermined control program for tracking in the telephoto cameras 12A and 12B, the telephoto cameras 12A and 12B are controlled by their own control. The person may be tracked.

  In the examples of FIGS. 17 and 18, the display screen of the display device 6 is displayed in four divisions, but each image may be displayed on the entire display screen of each of the four display devices.

  FIG. 19 is a diagram illustrating a situation where a plurality of monitoring devices 3 are installed in the communication base station 1. Monitoring devices 3 </ b> A to 3 </ b> D are installed along the outer periphery of the building of the communication base station 1. The monitoring devices 3A, 3B, 3C, and 3D monitor the monitoring areas 4A, 4B, 4C, and 4D, respectively. The monitoring devices 3 </ b> A to 3 </ b> D are connected to a communication network 160 built in the communication base station 1. A control device 161 that controls the monitoring devices 3A to 3D in an integrated manner is connected to the communication network 160.

  For example, it is assumed that an intruder who has entered the monitoring area 4A from outside the premises of the communication base station 1 moves from the monitoring area 4A to the monitoring area 4B. In this case, first, when the intruder is photographed by the monitoring device 3A, feature data relating to the intruder is generated by the feature data generating unit 24 provided in the monitoring device 3A. The feature data is notified to the control device 161 from the monitoring device 3A. When the intruder moves from the monitoring area 4A to the monitoring area 4B, the intruder is photographed by the monitoring device 3B, and feature data relating to the intruder is generated by the feature data generating unit 24 provided in the monitoring device 3B. The feature data is notified to the control device 161 from the monitoring device 3B. The control device 161 compares the feature data notified from the monitoring device 3A with the feature data notified from the monitoring device 3B, and if both feature data match (or approximate), the monitoring device 3A, The intruder photographed by 3B is specified as the same person. Then, a tracking command is input to the monitoring device 3B so that the intruder's automatic tracking performed by the telephoto camera 12A included in the monitoring device 3A is taken over by the telephoto camera 12A included in the monitoring device 3B. Thereby, automatic tracking of the intruder straddling the monitoring areas 4A and 4B is performed.

  As described above, according to the monitoring system 5 (and the monitoring apparatus 3) according to the present embodiment, the telephoto camera 12A is intruded when an intruder is included in the captured image captured by the wide-angle camera 11. By automatically tracking and photographing a person, an enlarged image 300 of the intruder is acquired and displayed on the display device 6. Thus, by automatically tracking and shooting the intruder into the monitoring area 4 with the telephoto camera 12A, the enlarged image 300 of the intruder can be taken without omission. Further, the telephoto camera 12B acquires an image of a desired location in the monitoring area 4 and displays it on the display device 6 by being remotely operated by an operator. Therefore, even when a plurality of intruders enter the monitoring area 4 at the same time, an intruder different from the intruder that is captured by the telephoto camera 12A can be captured by the telephoto camera 12B. As a result, a plurality of intruders can be photographed without omission.

  Further, according to the monitoring system 5 according to the present embodiment, the telephoto camera 12B performs imaging of a desired location by remote operation of the operator (manual imaging mode) and imaging of an intruder by automatic tracking (automatic tracking mode). Switching is possible. Therefore, when a plurality of intruders intrude into the monitoring area 4 at the same time, an operation of automatically tracking and photographing a plurality of intruders using the telephoto cameras 12A and 12B, and the intruders are automatically tracked by the telephoto camera 12A. Since the telephoto camera 12B can switch the operation of photographing another desired intruder while photographing, it is possible to improve user convenience.

  Further, according to the monitoring system 5 according to the present embodiment, the position in the monitoring area 4 photographed by the telephoto camera 12A, the position in the monitoring area 4 photographed by the telephoto camera 12B, and the monitoring area 4 A position information map 250 indicating the position of the intruder is displayed on the display device 6. Therefore, since the operator can easily identify the intruder to be photographed next by the telephoto camera 12B in the manual photographing mode based on the position information map 250, it is possible to photograph a plurality of intruders without omission. It becomes possible.

  Further, according to the monitoring system 5 according to the present embodiment, the material analysis unit 39A obtains spectra of specific wavelengths including the infrared region for the image regions 71 to 73 corresponding to the moving object in the photographed image 200A. Detecting and analyzing the material of the moving object based on the detection result. Therefore, when human skin, chemical fiber, or the like is included in the image areas 71 to 73 corresponding to the moving object as a result of the material analysis, the moving object can be identified as a human. As a result, when a moving object is included in the predetermined monitoring area 4, it is possible to accurately identify whether the moving object is a human being or an animal other than that. In addition, the feature data generation unit 24A generates the feature data representing the feature amount of the moving object including the parameter related to the material of the moving object analyzed by the material analysis unit 39A. Then, the tracking processing unit 44 automatically tracks the moving object based on the feature data. Therefore, each moving object that moves in the monitoring area 4 can be accurately tracked based on the feature data relating to each moving object.

  Further, according to the monitoring system 5 according to the present embodiment, as shown in FIG. 19, the automatic tracking of the moving object across the different monitoring areas 4A to 4D is accurately performed based on the feature data regarding each moving object. Can be done.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined not by the above-mentioned meaning but by the scope of claims for patent, and is intended to include all modifications within the scope and meaning equivalent to the scope of claims for patent.

3, 3A to 3D monitoring device 4, 4A to 4D monitoring area 5 monitoring system 6 display device 11A, 11B wide angle camera 12A, 12B telephoto camera 21 imaging unit 22 analysis unit 23, 23A, 23B identification unit 24, 24A, 24B characteristic data Generation unit 39A, 39B Material analysis unit 43 Position specifying unit 44 Tracking processing unit 250 Location information map

Claims (6)

A monitoring device;
A display device;
With
The monitoring device
First imaging means for imaging a predetermined monitoring area;
When a moving object is included in the captured image captured by the first imaging unit, the display device is configured to acquire an enlarged image of the moving object by automatically tracking and capturing the moving object. A second photographing means for displaying on
By being remotely operated by an operator, an image of a desired location in the monitoring area can be acquired and displayed on the display device independently of the first imaging unit and the second imaging unit. 3 shooting means;
Having a monitoring system.   The monitoring system according to claim 1, wherein the third imaging unit is capable of switching between imaging of a desired location by an operator's remote operation and imaging of a moving object by automatic tracking.   A position in the monitoring area being imaged by the second imaging means, a position in the monitoring area being imaged by the third imaging means, and a position of the moving object in the monitoring area; The monitoring system according to claim 1, wherein position information indicating is further displayed on the display device. When a moving object is included in the captured image captured by the first capturing unit, a spectrum of a plurality of specific wavelengths including an infrared region with respect to an image region corresponding to the moving object in the captured image. And material analysis means for analyzing the material of the moving object based on the detection result;
Data generation means for generating feature data representing the feature amount of the moving object, including parameters relating to the material of the moving object;
Further comprising
The monitoring system according to claim 1, wherein the moving object is automatically tracked based on the feature data. A plurality of the monitoring areas are photographed by a plurality of the monitoring devices,
The monitoring system according to claim 4, wherein automatic tracking of the moving object across different monitoring areas is performed based on the feature data. First imaging means for imaging a predetermined monitoring area;
When a moving object is included in a captured image captured by the first imaging unit, an enlarged image of the moving object is acquired by automatically tracking and capturing the moving object; Photographing means;
A third imaging unit that obtains an image of a desired location in the monitoring area independently from the first imaging unit and the second imaging unit by being remotely operated by an operator;
A monitoring device comprising:

Images