Detection device and detection method

Abstract

To correct the influence of a variation of the internal temperature of an infrared sensor with a simpler configuration.SOLUTION: A detection device comprises: an acquisition unit 10 that acquires the temperature distribution of a target area A measured by an infrared sensor 2 in which a plurality of infrared detection elements are two-dimensionally arranged; a processing unit 11 that, in the temperature distribution, calculates the amount of change in measured temperature between the infrared detection elements arranged in proximity to each other, and determines the grade distribution of the temperature distribution including the amount of change in measured temperature; a determination unit 12 that, based on the determined grade distribution, determines the presence or absence of an object to be detected present in the target area A; and a presentation unit 13 that presents a result of determination made by the determination unit 12.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a detection device and a detection method, and more particularly to a technique for detecting a living body. [Background technology]

[0002] Technologies for detecting objects in a specific area using infrared sensors have been known for some time. In particular, infrared sensors are used for human detection in a variety of applications, such as monitoring support that recognizes human movements while respecting privacy, intrusion detection in situations where it is difficult to use cameras, such as at night, and smart security, including preparation for unexpected incidents involving workers in factories, etc.

[0003] In conventional object detection technologies using infrared sensors, detection accuracy can be reduced due to fundamental factors. For example, the temperature accuracy of the infrared sensor can be reduced if a heat source is present near the location where the infrared sensor is installed, if hot or cold air is blowing on the infrared sensor body, or if the temperature of the infrared sensor body changes suddenly. In addition, the temperature accuracy of the infrared sensor can be reduced if there is an object that does not easily transmit far infrared rays, such as glass, acrylic, or water vapor, between the infrared sensor and the object to be detected, or if foreign matter or water droplets that do not easily transmit far infrared rays are attached to the lens of the infrared sensor body.

[0004] For example, Patent Document 1 discloses a two-dimensional infrared array sensor with a built-in correction circuit that calculates and corrects temperature drift that occurs within the two-dimensional infrared array sensor due to changes over time and changes in environmental temperature. The correction circuit disclosed in Patent Document 1 corrects the output of pixel rows in the measurement mode of the infrared array sensor using output data of the pixel rows in a state without temperature drift at the time of initial setup of the infrared array sensor, and outputs the corrected digital data from the infrared array sensor. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-83534 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology disclosed in Patent Document 1 has a configuration in which a correction circuit having a CPU and a volatile memory is built into the infrared sensor, which makes the configuration of the infrared sensor more complicated.

[0007] The present invention has been made to solve the above-mentioned problems, and has an object to correct the influence of fluctuations in the internal temperature of an infrared sensor with a simpler configuration. [Means for solving the problem]

[0008] In order to solve the above-mentioned problems, the detection device of the present invention includes an acquisition unit that acquires a temperature distribution in a target area measured by a sensor in which a plurality of infrared detection elements are arranged two-dimensionally; a processing unit that calculates the amount of change in measured temperature between infrared detection elements arranged closely to each other in the temperature distribution and obtains a gradient distribution of the temperature distribution including the amount of change in measured temperature; a determination unit that determines whether or not a detection target object is present in the target area based on the obtained gradient distribution; and a presentation unit that presents the determination result by the determination unit.

[0009] In addition, in the detection device of the present invention, the determination unit may determine that the object is present in the target area if the magnitude of at least one of the measured temperature change amounts included in the gradient distribution exceeds a threshold value set for the temperature of the object.

[0010] Furthermore, in the detection device according to the present invention, the processing unit may calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in a first direction in the temperature distribution to obtain a first gradient distribution, and may calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in a second direction perpendicular to the first direction to obtain a second gradient distribution, and the determination unit may determine that the object is present in the target area if the magnitude of the amount of change in at least one measured temperature in either the first gradient distribution or the second gradient distribution exceeds the threshold value.

[0011] Furthermore, the detection device according to the present invention may further include a removal unit that removes from the gradient distribution, in the time-lapse data of the gradient distribution, the amount of change in measured temperature between infrared detection elements where the amount of change in the measured temperature increases over time at a predetermined rate of increase, as a heat source other than the object, and the determination unit determines the presence or absence of the object in the target area based on the gradient distribution from which the heat sources other than the object have been removed by the removal unit, and the predetermined rate of increase may be a rate of increase different from the rate of increase in the amount of change in measured temperature related to the object.

[0012] In addition, in the detection device of the present invention, the temperature distribution is a temperature distribution obtained by capturing the temperature of the target area in a three-dimensional region on a two-dimensional plane, and the sensor may be arranged so as to be directed toward the floor surface of the target area.

[0013] In the detection device according to the present invention, the object may include a living organism.

[0014] In order to solve the above-mentioned problems, the detection method of the present invention includes a first step of acquiring a temperature distribution in a target area measured by a sensor having a plurality of infrared detection elements arranged two-dimensionally; a second step of calculating the amount of change in measured temperature between infrared detection elements arranged closely to each other in the temperature distribution and determining a gradient distribution of the temperature distribution including the amount of change in measured temperature; a third step of determining the presence or absence of a detection target object present in the target area based on the determined gradient distribution; and a fourth step of presenting the determination result of the third step.

[0015] In addition, in the detection method of the present invention, the third step may determine that the object is present in the target area if the magnitude of at least one of the changes in the measured temperature included in the gradient distribution exceeds a threshold value set for the temperature of the object.

[0016] Furthermore, in the detection method according to the present invention, the second step may calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in a first direction in the temperature distribution to obtain a first gradient distribution, and calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in a second direction perpendicular to the first direction to obtain a second gradient distribution, and the third step may determine that the object is present in the target area if the magnitude of the amount of change in at least one measured temperature in either the first gradient distribution or the second gradient distribution exceeds the threshold value. [Effects of the Invention]

[0017] According to the present invention, in the temperature distribution of a target area measured by a sensor having multiple infrared detection elements arranged two-dimensionally, the amount of change in measured temperature between infrared detection elements arranged close to each other is calculated, and the gradient distribution of the temperature distribution, including the amount of change in measured temperature, is determined.Therefore, the influence of fluctuations in the internal temperature of the infrared sensor can be corrected with a simpler configuration. [Brief explanation of the drawings]

[0018] [Figure 1] FIG. 1 is a block diagram showing the configuration of a detection device according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a block diagram illustrating a hardware configuration of the detection device according to the first embodiment. [Figure 3] FIG. 3 is a schematic diagram showing an example of a target area that is a detection range of the detection device according to the first embodiment. [Figure 4A] FIG. 4A is a diagram for explaining an example of a temperature distribution acquired by the detection device according to the first embodiment. [Figure 4B] FIG. 4B is a diagram for explaining an example of a temperature distribution acquired by the detection device according to the first embodiment. [Figure 4C] FIG. 4C is a diagram for explaining an example of a temperature distribution acquired by the detection device according to the first embodiment. [Figure 4D] FIG. 4D is a diagram for explaining an example of a temperature distribution acquired by the detection device according to the first embodiment. [Figure 5] FIG. 5 is a diagram showing an example of measurements taken by the infrared sensor in one day and acquired by the detection device according to the first embodiment. [Figure 6] FIG. 6 is a diagram showing an example of the temperature in the main body of the infrared sensor used in the detection device according to the first embodiment. [Figure 7] FIG. 7 is a diagram for explaining the influence of air conditioning equipment on the detection device according to the first embodiment. [Figure 8] FIG. 8 is a diagram showing an example of a gradient distribution obtained by the detection device according to the first embodiment. [Figure 9] FIG. 9 is a flowchart illustrating the operation of the detection device according to the first embodiment. [Figure 10] FIG. 10 is a diagram for explaining the effect of the detection device according to the first embodiment. [Figure 11] FIG. 11 is a block diagram showing the configuration of a detection device according to the second embodiment. [Figure 12]FIG. 12 is a flowchart illustrating the operation of the detection device according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0019] Preferred embodiments of the present invention will be described in detail below with reference to Figures 1 to 12. In the present embodiments, the object to be detected will be described as a person, by way of example.

[0020] [Summary of the Invention] First, an outline of the invention according to this embodiment will be described.

[0021] The detection device 1 according to this embodiment corrects for the influence of fluctuations in the internal temperature of the infrared sensor 2 installed in the target area A, and detects people present in the target area A. In particular, in this embodiment, the correction is performed by focusing on the relationship between the change in the internal temperature of the infrared sensor 2 accompanying a change in the environmental temperature and the characteristics of the change in temperature distribution measured under the same conditions.

[0022] As shown in Figure 1, the detection device 1 is communicatively connected to an infrared sensor 2, and acquires and processes the temperature distribution in the target area A measured by the infrared sensor 2, and further detects whether or not a person is present in the target area A.

[0023] The infrared sensor 2 used in this embodiment is a two-dimensional infrared array sensor that uses 64 infrared detection elements arranged in 8 rows and 8 columns to form an 8x8 pixel matrix. The infrared sensor 2 can detect temperature changes within a three-dimensional target area A on a two-dimensional plane, and the position of each of the 64 pixels is used as two-dimensional position coordinates within the three-dimensional target area A. The temperature distribution for each frame can be obtained from the detected intensity of infrared energy at each pixel. The frame rate of the infrared sensor 2 is 1 frame per second, the temperature range that each infrared detection element can measure is 0 to 80°C, and the temperature resolution is 0.25°C.

[0024] The target area A is, for example, an area such as a conference room in a building, and the entire target area A is covered by the infrared sensor 2's 60° vertical and horizontal viewing angle. FIG. 3 is a schematic diagram showing an example of the target area A, specifically a plan view of the conference room as viewed vertically. In this embodiment, the infrared sensor 2 is disposed on a wall surface near the ceiling of the target area A, which is a conference room in a building, so as to be oriented toward the floor. Therefore, the infrared sensor 2 can measure temperature changes within the target area A at a position of 8×8 pixels (64 pixels) in vertical and horizontal directions, as two-dimensional position coordinates corresponding to the floor. The target area A is equipped with a desk, chairs a, b, c, and d, a monitor, and a shelf, and a partition is placed on the desk. A person to be detected enters and exits the target area A through the entrance. In addition, an air conditioning outlet (not shown) is embedded in the ceiling of the target area A.

[0025] 4A to 4D are diagrams showing the temperature distribution in target area A measured by infrared sensor 2 when people sat on chairs a, b, c, and d in target area A, in an 8x8, 64-pixel pixel matrix. The ambient temperature in target area A was measured to be in the range of approximately 18.50°C to 20.25°C.

[0026] FIG. 4A shows the temperature distribution measured when a person is sitting in chair a, i.e., a thermal image seen from infrared sensor 2. At the pixel position enclosed in a square corresponding to the position of chair a, a temperature of 22.5°C is measured, indicating that a person has been detected. FIG. 4B shows the temperature distribution measured when a person is sitting in chair b, indicating that a temperature of 21.5°C is measured at the pixel position enclosed in a square corresponding to the position of chair b, indicating that a person has been detected. FIG. 4C shows the temperature distribution measured when a person is sitting in chair c, indicating that a temperature of 21.75°C is measured at the pixel position enclosed in a square corresponding to the position of chair c, indicating that a person has been detected.

[0027] In this way, at locations where people are present in target area A, temperatures measured are 2 to 3 degrees Celsius higher than the ambient temperature.

[0028] Here, the effect that changes in the environmental temperature within target area A have on the measurement values of infrared sensor 2 will be described with reference to Fig. 5. Fig. 5 shows the temperatures measured in one day by an infrared detection element facing toward the ceiling, where people within target area A are not visible, out of a total of 64 pixels in an 8x8 configuration of infrared sensor 2. The pixel corresponding to this infrared detection element is pixel e (hereinafter referred to as "pixel 64"), which is located at the 64th position surrounded by a dotted line in the pixel matrix of Fig. 4A.

[0029] As shown in Figure 5, the measured temperature of pixel 64 is a pixel associated with a position where no human beings are detected, but the fluctuations in the measured temperature are particularly large during the daytime. During the daytime when the fluctuations in the measured temperature are more severe, the air conditioning equipment was in operation, and also from a comparison with the room temperature data, it is believed that the measured temperature at the position of pixel 64 is influenced by the air supply from the air conditioning equipment outlet.

[0030] Furthermore, when the temperature of the infrared sensor 2 itself is measured using a thermistor attached to the infrared sensor 2, it is found that the temperature of the infrared sensor 2 itself changes significantly during the hours when the air conditioning equipment is operating, as shown in Figure 6. From this, it is thought that one of the factors behind the fluctuations in the measured temperature of pixel 64 is the fluctuation in the temperature of the infrared sensor 2 itself caused by the operation of the air conditioning equipment. As mentioned above, in principle, the measurement accuracy of temperature measurements using an infrared sensor is said to decrease when the sensor body is exposed to hot or cold air or when the temperature of the sensor body changes suddenly.

[0031] Figure 7(c) shows the internal temperature of the infrared sensor 2 measured during the time range of 13:00 to 15:00 when the air conditioning equipment was operating. Figure 7(a) and (c) show thermal images of the temperature distribution in the target area A measured by the infrared sensor 2 at 13:47 and 13:52, respectively, as indicated by the dotted lines in Figure 7.

[0032] As shown in Figure 7(c), the internal temperature of infrared sensor 2 rose by approximately 2°C over the five minutes from 13:47 to 13:52. Comparing the temperature distribution measured by infrared sensor 2 at 13:47 (Figure 7(a)) with the temperature distribution measured by infrared sensor 2 five minutes later at 13:52 (Figure 7(b)), it is clear that the measured temperature has risen by approximately 3°C throughout the entire temperature distribution shown by a total of 64 pixels. In particular, it can be seen that in the temperature distribution shown by the pixel matrix of a total of 64 pixels, the rise in measured temperature is equivalent for each pixel and its neighboring pixels.

[0033] As mentioned above, the presence of a person is detected as a temperature rise of 2 to 3°C above the ambient temperature. However, as shown in Figure 7, when the air conditioning equipment is operating, the fluctuation in the measured temperature due to changes in the internal temperature of the infrared sensor 2 caused by the air supply from the air conditioning equipment hitting the body of the infrared sensor 2 is greater than the temperature change caused by the presence of a person. This means that the detection accuracy in detecting a person decreases. In other words, since the measured temperature of the infrared sensor 2 varies significantly depending on the internal temperature of the infrared sensor 2, it is necessary to correct for the influence of the internal temperature.

[0034] Therefore, the detection device 1 according to an embodiment of the present invention corrects the influence of the internal temperature of the infrared sensor 2, focusing on the fact that the influence of the air supply from the air conditioning equipment within the target area A on the change in the internal temperature of the infrared sensor 2 is roughly the same for each pixel.

[0035] Specifically, the gradient is calculated by calculating the temperature difference between closely spaced pixels in the two-dimensional temperature distribution of the target area A measured by the infrared sensor 2. Figure 8 (a) shows the temperature distribution of the target area A measured by the infrared sensor 2 at two different times, 13:47 and 13:52. The temperature distribution at 13:52 is 2 to 4°C higher overall than the temperature distribution at 13:47 due to an increase in the internal temperature of the infrared sensor 2. Therefore, in an 8x8 pixel matrix, the gradient distribution is calculated by taking the amount of change, or difference, in measured temperatures between closely spaced pixels in the row direction (hereinafter sometimes referred to as the "horizontal direction") and / or column direction (hereinafter sometimes referred to as the "vertical direction"). For example, the difference in measured temperature between a given pixel and its two neighboring pixels in the horizontal direction can be calculated. This is based on the fact that it is more appropriate to calculate the gradient by taking the difference in measured temperature between a pixel in a position where a person is present in the target area A and a pixel in a position where no person is present, i.e., a pixel not affected by the presence of a person.

[0036] Figure 8(b) shows the gradient distribution obtained by taking the horizontal difference between the temperature distribution at 13:47 and the temperature distribution at 13:52, and the gradient distribution at each time has similar values. This shows that the effect of changes in the internal temperature of infrared sensor 2 due to factors such as air supply from the air conditioning equipment hitting infrared sensor 2 can be corrected by calculating the difference in measured temperatures between pixels arranged closely to each other in the temperature distribution and generating a gradient map.

[0037] In this way, the detection device 1 according to the embodiment of the present invention calculates the gradient distribution of the temperature distribution measured by the infrared sensor 2, and further determines whether or not a person is present in the target area A based on the calculated gradient distribution, thereby correcting for the influence of changes in the internal temperature of the infrared sensor 2 and detecting a person present in the target area A.

[0038] [First embodiment] Next, the configuration of the detection device 1 according to the first embodiment, which includes a function for correcting the influence of fluctuations in the internal temperature of the infrared sensor 2 described above, will be described with reference to the block diagram of FIG.

[0039] As shown in FIG. 1, the detection device 1 includes an acquisition unit 10, a processing unit 11, a determination unit 12, a presentation unit 13, and a storage unit 14.

[0040] The acquisition unit 10 acquires the temperature distribution in the target area A measured by an infrared sensor 2 (sensor) in which multiple infrared detection elements are arranged two-dimensionally. Specifically, the acquisition unit 10 acquires, via a wired or wireless connection, the temperature distribution measured by the infrared sensor 2 arranged in the target area A using 64 infrared detection elements arranged in 8 rows and 8 columns, and shown as a pixel matrix configuration of 64 pixels in total in an 8x8 matrix.

[0041] The processing unit 11 calculates the amount of change in the measured temperature between the infrared detection elements arranged close to each other in the temperature distribution acquired by the acquisition unit 10, and obtains a gradient distribution including the amount of change in the measured temperature.

[0042] Specifically, the processing unit 11 can calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in the horizontal direction (first direction) in the temperature distribution to obtain a gradient distribution (first gradient distribution), and can calculate the amount of change in measured temperature between infrared detection elements arranged close to each other in the vertical direction (second direction perpendicular to the first direction) to obtain a gradient distribution (second gradient distribution).

[0043] For example, in a temperature distribution of a pixel matrix configuration of 64 pixels, the processing unit 11 can calculate the difference in measured temperature between a pixel and its two adjacent pixels in the horizontal and / or vertical directions, and generate a gradient distribution including the difference.

[0044] The determination unit 12 determines whether or not a person to be detected exists in the target area A based on the gradient distribution obtained by the processing unit 11. Specifically, the determination unit 12 determines that a person exists in the target area A when the magnitude of at least one of the amounts of change in the measured temperatures included in the gradient distribution obtained by the processing unit 11 exceeds a threshold value set for the body temperature of the person to be detected.

[0045] For example, if the absolute value of the difference in the measured temperatures included in the gradient distribution is 2.0°C or more, the determination unit 12 can determine that a person is present in the target area A. Furthermore, if the magnitude of the change in at least one measured temperature, that is, the absolute value of the difference, is 2.0°C or more in either the vertical gradient distribution or the horizontal gradient distribution, the determination unit 12 can determine that a person is present in the target area A.

[0046] The presentation unit 13 presents the determination result by the determination unit 12. The presentation unit 13 can present the determination result, for example, on a display screen (not shown) or on an external terminal device. Furthermore, the presentation unit 13 can present a preset alarm based on the determination result as text, image, or audio information on a display screen, speaker, or the like of its own device or an external terminal. For example, if a person is detected in the target area A during a preset detection period, such as at night, an alarm indicating a risk of intrusion can be issued. Alternatively, the determination result can be sent to an external terminal or the like periodically, such as once every hour, to check the usage status of a conference room or the like.

[0047] The storage unit 14 stores the temperature distribution of the target area A acquired by the acquisition unit 10, the gradient distribution calculated by the processing unit 11, and a threshold value used by the determination unit 12 to determine whether or not a person is present. Furthermore, the storage unit 14 stores information used by the presentation unit 13 to present the determination result.

[0048] [Hardware configuration of the detection device] Next, an example of a hardware configuration for realizing the detection device 1 having the above-described functions will be described with reference to FIG.

[0049] 2, the detection device 1 can be realized by, for example, a computer including a processor 102, a main memory device 103, a communication interface 104, an auxiliary memory device 105, and an input / output (I / O) 106, which are connected via a bus 101, and a program that controls these hardware resources. The detection device 1 can also include a display device 107 connected via the bus 101. The detection device 1 is also connected to the above-mentioned infrared sensor 2 via the bus 101.

[0050] The main memory device 103 stores in advance programs for the processor 102 to perform various controls and calculations. The processor 102 and the main memory device 103 implement the functions of the processing unit 11 and the determination unit 12 shown in FIG.

[0051] The communication interface 104 is an interface circuit for connecting the detection device 1 to various external electronic devices via a network. The presentation unit 13 described in Fig. 1 may be configured to transmit the determination result to an external terminal from the communication interface 104 via the network NW.

[0052] The auxiliary storage device 105 is composed of a readable / writable storage medium and a drive for reading and writing various information such as programs and data from and to the storage medium. The auxiliary storage device 105 can use a semiconductor memory such as a hard disk or flash memory as the storage medium.

[0053] The auxiliary storage device 105 has a program storage area for storing the detection program executed by the detection device 1. The auxiliary storage device 105 realizes the storage unit 14 described in FIG. 1. The auxiliary storage device 105 also stores information about the threshold value, information about the target area A, and information about the infrared sensor 2. Furthermore, the auxiliary storage device 105 may have, for example, a backup area for backing up the above-mentioned data, programs, etc.

[0054] The input / output I / O 106 is configured by an I / O terminal for inputting signals from an external device and outputting signals to an external device.

[0055] The display device 107 is configured by an organic EL display, a liquid crystal display, etc. The display device 107 can also realize the presentation unit 13 described in FIG.

[0056] Here, the program stored in the program storage area of the auxiliary storage device 105 may be a program that is processed in chronological order according to the detection method described in this specification, or may be a program that is processed in parallel, or at a required timing such as when called. Furthermore, the program may be processed by one computer, or may be processed in a distributed manner by multiple computers.

[0057] [Detection device operation] FIG. 9 is a flowchart showing the operation of the detection device 1 according to this embodiment. Infrared sensor 2 is installed in target area A in advance, and the following process is started.

[0058] First, the acquisition unit 10 acquires the temperature distribution of the target area A measured by the infrared sensor 2 (step S1). The infrared sensor 2 is a two-dimensional infrared array sensor, and the acquired temperature distribution is, for example, a two-dimensional temperature distribution of the target area A in a pixel matrix configuration of 8x8 pixels vertically and horizontally, or a total of 64 pixels.

[0059] Next, the processing unit 11 calculates the amount of change in measured temperature between pixels arranged closely to each other in the temperature distribution of the target area A acquired in step S1, and determines a gradient distribution including the amount of change in measured temperature (step S2). More specifically, the processing unit 11 can determine the gradient distribution by calculating the difference in measured temperature between a given pixel and its two adjacent pixels in the horizontal direction in the temperature distribution of a pixel matrix having a total of 64 pixels, with an 8x8 configuration. Similarly, the processing unit 11 can determine the gradient distribution by calculating the difference in measured temperature between a given pixel and its two adjacent pixels in the vertical direction in the temperature distribution of a 64-pixel pixel matrix.

[0060] Next, the determination unit 12 determines whether or not a person to be detected is present in the target area A based on the gradient distribution of the target area A obtained in step S2 (step S3). Specifically, the determination unit 12 can perform threshold processing to determine the presence or absence of a person in the target area A. For example, the determination unit 12 can determine that a person is present in the target area A if the absolute value of at least one of the absolute values of the differences in the measured temperatures included in either the horizontal gradient distribution or the vertical gradient distribution is 2.0°C or greater. The specific value of the threshold can be set according to the characteristics of the heat source to be detected. Furthermore, the determination unit 12 may be configured to output a determination result indicating that a person to be detected is present when both the horizontal gradient distribution and the vertical gradient distribution have values equal to or greater than the threshold. Alternatively, the determination unit 12 may perform the determination process using only the gradient distribution in one direction, either the horizontal or vertical direction.

[0061] Next, the presentation unit 13 presents the determination result obtained in step S4 (step S4). For example, when the determination result indicates that a person is present in the target area A, the presentation unit 13 can issue an alarm to the display device 107 or an external terminal.

[0062] Next, the effects of the detection device 1 according to the present embodiment will be described with reference to Fig. 10. The upper part of Fig. 10 shows the determination results output by the detection device 1 over a one-day period in a conference room in target area A. The lower part of Fig. 10 shows, for comparison, the lighting status detected by an illuminance sensor in the same conference room over the same period.

[0063] As shown in Figure 10, the lighting status of the conference room indicated by the illuminance sensor during the time period from 9:00 to 19:00 matches the determination result of the person detection by the detection device 1. Here, between 6:00 and 9:00, only the illuminance sensor detected the lighting status "lights on" and the detection device 1 did not detect any person, but this is because only the lights were on for security patrols and no one was in the conference room. This also shows that the detection device 1 accurately detected a situation where the lights were on but no one was present.

[0064] As described above, the detection device 1 according to the first embodiment calculates the amount of change in measured temperature between infrared detection elements arranged closely to each other in the temperature distribution of the target area A measured by the infrared sensor 2 having a plurality of infrared detection elements arranged two-dimensionally, and determines the gradient distribution of the temperature distribution including the amount of change in measured temperature, thereby making it possible to correct the influence of fluctuations in the internal temperature of the infrared sensor 2 with a simpler configuration. Furthermore, as a result, the detection device 1 can detect the target person with higher accuracy.

[0065] Furthermore, because the detection device 1 according to this embodiment can detect people with higher accuracy, it can be used in place of detection devices using visible cameras in situations where conventional infrared sensors are difficult to use due to their lack of detection accuracy and therefore visible cameras are used. Furthermore, the detection device 1 according to this embodiment can be used, for example, to check the presence of people in restrooms, rental spaces, conference rooms, and other areas of commercial and public facilities where it is difficult to install cameras due to privacy concerns, as well as to check the safety of elderly people and factory workers. It can also be used as a detection system for facility and perimeter security in situations where it is difficult to use visible cameras, such as at night, thereby enabling labor savings in a variety of situations.

[0066] [Second embodiment] Next, a second embodiment of the present invention will be described. In the following description, the same components as those in the first embodiment will be denoted by the same reference numerals, and the description thereof will be omitted.

[0067] In the first embodiment, the processing unit 11 calculates the difference in measured temperature between pixels arranged close to each other in the temperature distribution of the target area A to obtain a gradient distribution, and the determination unit 12 determines the presence or absence of a person in the target area A based on the gradient distribution. In contrast, the second embodiment further includes a removal unit 15 that removes specific heat sources other than the person being detected from the gradient distribution.

[0068] [Detection device functional block] Fig. 11 is a block diagram showing the configuration of a detection device 1A according to the second embodiment. As shown in Fig. 11, the detection device 1A is communicably connected to an infrared sensor 2 having a two-dimensional infrared array. The detection device 1A includes an acquisition unit 10, a processing unit 11, a determination unit 12, a presentation unit 13, a storage unit 14, and a removal unit 15. The following description will focus on the configuration that differs from the first embodiment.

[0069] The removal unit 15 removes, from the gradient distribution time data obtained by the processing unit 11, the amount of change in measured temperature between infrared detection elements where the amount of change in measured temperature increases over time at a predetermined rate, as a heat source other than a person. The predetermined rate of increase is an increase rate different from the increase rate of the amount of change in measured temperature of the "person" being detected. In this embodiment, the predetermined rate of increase is described as a case where the increase rate is slower than the increase over time in measured temperature at a position where a person is present.

[0070] More specifically, the removal unit 15 is configured to remove in advance specific heat sources other than people placed in the target area A. Examples of heat sources other than people include the monitor shown in FIG. 3 . The removal unit 15 removes these specific heat sources from the gradient distribution in advance. Generally, when a person is present in the target area A, the measured temperature at the position where the person is present rises relatively rapidly. On the other hand, among objects other than the detection target, such as monitors, there are heat sources whose temperature rises more slowly than that of a person. In such a case, the removal unit 15 removes in advance the heat sources other than people, and the determination unit 12 can determine the presence or absence of a person in the target area A based on the gradient distribution from which the heat sources other than people have been removed.

[0071] In addition, the heat sources to be removed by the removal unit 15 may not only be heat sources whose temperature increases more slowly than the increase in the measured temperature over time at a location where people are present, but also heat sources that do not move and are fixed in position in the target area A.

[0072] [Detection device operation] Next, the operation of the detection device 1A having the above-described configuration will be described with reference to the flowchart of Fig. 12. The infrared sensor 2 is installed in the target area A, and the following process is started.

[0073] First, the acquisition unit 10 acquires the temperature distribution of the target area A measured by the infrared sensor 2 (step S1). The infrared sensor 2 is a two-dimensional infrared array sensor, and the acquired temperature distribution is, for example, a two-dimensional temperature distribution of the target area A having a pixel matrix configuration of 8×8 pixels in length and width, totaling 64 pixels, measured at a frame rate of 1 frame / second.

[0074] Next, the processing unit 11 calculates the amount of change in measured temperature between pixels arranged closely to each other in the temperature distribution of the target area A acquired in step S1, and obtains a gradient distribution including the amount of change in measured temperature (step S2). More specifically, the processing unit 11 calculates the difference in measured temperature between a given pixel and its two adjacent pixels in the horizontal direction in the temperature distribution of a pixel matrix having a total of 64 pixels in an 8x8 configuration. Similarly, the processing unit 11 can calculate the difference in measured temperature between a given pixel and its two adjacent pixels in the vertical direction in the temperature distribution of a 64-pixel pixel matrix to obtain a gradient distribution.

[0075] Next, the removal unit 15 removes, from the gradient distribution, specific heat sources whose measured temperatures increase over time at a predetermined rate in the time-series data of the gradient distribution obtained by the processing unit 11, which are different from the rate of increase of the measured temperatures at positions where "people" are present, as heat sources other than people (step S20). Specifically, the removal unit 15 removes, from the gradient distribution, information about known heat sources, such as monitors whose measured temperatures increase more slowly compared to the relatively rapid increases in measured temperatures that occur at positions where people are present. Note that the removal unit 15 may identify the presence of specific heat sources other than people to be removed, based on the time-series data of the temperature distribution of the target area A acquired by the acquisition unit 10 in step S1.

[0076] Next, the determination unit 12 determines whether or not a person is present in the target area A based on the gradient distribution from which heat sources other than people have been removed by the removal unit 15 in step S20 (step S3). For example, the determination unit 12 can determine that a person is present in the target area A if the absolute value of at least one of the absolute values of the differences in measured temperatures included in either the horizontal gradient distribution or the vertical gradient distribution is 2.0°C or greater.

[0077] Next, the presentation unit 13 presents the determination result obtained in step S4 (step S4). For example, when the presentation unit 13 obtains a determination result indicating that a person is present in the target area A, the presentation unit 13 can present an alert to the display device 107 or an external terminal.

[0078] As described above, according to the detection device 1A of the second embodiment, specific heat sources other than the person to be detected are removed in advance, so the detection device 1A can detect people with higher accuracy.

[0079] In the described embodiment, the object to be detected is a person, but the object may also be a living organism other than a human, such as an animal, or any other heat source, as long as it can detect temperature differences or temperature changes in the surrounding environment.

[0080] Furthermore, in the embodiment described above, a case where the cause of a change in the internal temperature of the infrared sensor 2 is, in particular, the air supply from an air conditioning system hitting the main body of the infrared sensor 2 has been described as an example. However, the cause of a change in the internal temperature of the infrared sensor 2 is not limited to the air supply from an air conditioning system. For example, factors other than air conditioning systems may also be included that have the same effect on a certain pixel and its neighboring pixels in the temperature distribution of the target area A, and that do not result in a large difference in the measured temperatures of each pixel when no one is present in the target area A.

[0081] In the embodiment described above, the gradient distribution is calculated from the temperature distribution in the target area A by calculating the difference in the measured temperature between a pixel and its two neighboring pixels. However, the gradient calculation is not limited to the difference between two neighboring pixels, as long as it can calculate the difference in the measured temperature between a pixel whose measured temperature is affected by the presence of a person and a pixel in a position where no person is present. For example, it may be the difference between adjacent pixels. Furthermore, the gradient calculation method can also use, for example, a first-order differential filter with a horizontal and / or vertical kernel (3 × 3). Furthermore, the filter only needs to satisfy the requirement that the sum of the weights is 0. By designing a filter according to the characteristics of the heat source, it is possible to use, for example, a filter that emphasizes heat sources that appear long vertically or long horizontally in the temperature distribution.

[0082] In the embodiment described above, all functional units are provided in one detection device 1. However, the functional units provided in the detection device 1 can be configured not only as a single computer but also as distributed units over a network.

[0083] The above describes embodiments of the detection device and detection method of the present invention, but the present invention is not limited to the described embodiments, and various modifications that a person skilled in the art can make within the scope of the invention described in the claims are possible. [Explanation of symbols]

[0084] 1...detection device, 2...infrared sensor, 10...acquisition unit, 11...processing unit, 12...determination unit, 13...presentation unit, 14...memory unit, 101...bus, 102...processor, 103...main memory device, 104...communication interface, 105...auxiliary memory device, 106...input / output I / O, 107...display device, NW...network.

Claims

1. an acquisition unit that acquires a temperature distribution of a target area measured by a sensor having a plurality of infrared detection elements arranged two-dimensionally; a processing unit that calculates a change in measured temperature between infrared detection elements arranged close to each other in the temperature distribution, and obtains a gradient distribution of the temperature distribution including the change in measured temperature; a determination unit that determines whether or not a detection target object exists in the target area based on the obtained gradient distribution; a presentation unit that presents a determination result by the determination unit; Equipped with a removal unit that compares the gradient distributions over a plurality of points in time and removes, from the gradient distribution, a change in the measured temperature between the infrared detection elements in which the change in the measured temperature increases at a predetermined rate over time, as a heat source other than the object; the determination unit determines whether the object exists in the target area based on a gradient distribution from which heat sources other than the object have been removed by the removal unit; and The predetermined increase rate is different from the increase rate of the change in the measured temperature of the object. Detection device.

2. 2. The detection device according to claim 1, The determination unit determines that the object is present in the target area when the magnitude of at least one of the amounts of change in the measured temperatures included in the gradient distribution exceeds a threshold value set for the temperature of the object. A detection device characterized by:

3. 3. The detection device according to claim 2, the processing unit calculates a change in measured temperature between infrared detection elements arranged adjacent to each other in a first direction in the temperature distribution to obtain a first gradient distribution, and calculates a change in measured temperature between infrared detection elements arranged adjacent to each other in a second direction perpendicular to the first direction to obtain a second gradient distribution; The determination unit determines that the object is present in the target area when the magnitude of the amount of change in at least one measured temperature in either the first gradient distribution or the second gradient distribution exceeds the threshold value. A detection device characterized by:

4. 4. The detection device according to claim 1, the temperature distribution is a temperature distribution obtained by capturing the temperature of the target area in a three-dimensional region on a two-dimensional plane, The sensor is positioned to point toward the floor of the target area. A detection device characterized by:

5. 5. The detection device according to claim 1, The object includes a living body. A detection device characterized by:

6. A first step of acquiring a temperature distribution of a target area measured by a sensor having a plurality of infrared detection elements arranged two-dimensionally; a second step of calculating a change in measured temperature between infrared detection elements arranged close to each other in the temperature distribution, and determining a gradient distribution of the temperature distribution including the change in measured temperature; a third step of determining whether or not a detection target object exists in the target area based on the obtained gradient distribution; a fourth step of presenting the determination result in the third step; Equipped with a fifth step of comparing the gradient distributions over a plurality of points in time, and removing from the gradient distribution, a change in the measured temperature between the infrared detection elements in which the change in the measured temperature increases at a predetermined rate over time, as a heat source other than the object; the third step determines whether or not the object exists in the target area based on the gradient distribution from which heat sources other than the object have been removed in the fifth step; The predetermined increase rate is different from the increase rate of the change in the measured temperature of the object. Detection method.

7. 7. The detection method according to claim 6, In the third step, when the magnitude of at least one of the variations in the measured temperatures included in the gradient distribution exceeds a threshold value set for the temperature of the object, it is determined that the object is present in the target area. A detection method characterized by:

8. 8. The detection method according to claim 7, the second step calculates a change in measured temperature between infrared detection elements arranged adjacent to each other in a first direction in the temperature distribution to obtain a first gradient distribution, and calculates a change in measured temperature between infrared detection elements arranged adjacent to each other in a second direction perpendicular to the first direction to obtain a second gradient distribution; In the third step, when the magnitude of the amount of change in at least one measured temperature in either the first gradient distribution or the second gradient distribution exceeds the threshold value, it is determined that the object is present in the target area. A detection method characterized by:

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