Displacement measurement device, displacement measurement system, non-contact input device, and biological micromotion measurement device

Abstract

To provide a displacement measuring device that can reduce an arithmetic load and quickly detect the displacement of a measurement object.SOLUTION: A displacement measuring device comprises: irradiation means that irradiates a measurement object with coherent light; luminance change coordinate detection means that detects luminance change coordinates where a luminance change occurs based on light reflected from the measurement object, and outputs data related to the luminance change coordinates; and displacement estimation means that estimates the displacement of the measurement object based on the data related to the luminance change coordinates output by the luminance change coordinate detection means. The displacement estimation means has a first numerical sequence processing system that performs arithmetic processing on a first numerical sequence including a set of first elements each representing the position of the luminance change coordinates extracted from the data to calculate the displacement of the first elements of the measurement object, and a second numerical sequence processing system that performs arithmetic processing on a second numerical sequence including a set of second elements each representing the position of the luminance change coordinates extracted from the data to calculate the displacement of the second elements of the measurement object.SELECTED DRAWING: Figure 9

Description

[Technical Field]

[0001] The present invention relates to a displacement amount measuring device, a displacement amount measuring system, a non-contact input device, and a biological micromotion measuring device. [Background technology]

[0002] Non-Patent Document 1 listed below discloses a technology for measuring minute displacements of an object by acquiring a speckle pattern using an event-based vision sensor, generating a speckle pattern image, and then performing image processing on the image to measure minute displacements of the object. Summary of the Invention [Problem to be solved by the invention]

[0003] However, in conventional displacement measurement techniques using an event-based vision sensor and speckle pattern images, event information output asynchronously from a photodetector element is stored for a certain period of time, and then imaged to apply conventional image processing to calculate the translational amount of the speckle pattern image.As a result, despite the use of an event-based vision sensor, the amount of calculation required is relatively large, and the amount of displacement of the object cannot be detected quickly.

[0004] In order to solve the above-mentioned problems of the conventional technology, an object of the present invention is to realize a displacement amount measuring device that can reduce the calculation load and detect the displacement amount of a measurement object at high speed. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, one embodiment of a displacement measuring device includes an irradiation means for irradiating a measured object with coherent light, a brightness change coordinate detection means for detecting brightness change coordinates where a brightness change has occurred based on the light reflected by the measured object and outputting data related to the brightness change coordinates, and a displacement estimation means for estimating a displacement of the measured object based on the data related to the brightness change coordinates output from the brightness change coordinate detection means, wherein the displacement estimation means has a first numerical sequence processing system for calculating a displacement of a first element of the measured object by performing arithmetic processing on a first numerical sequence consisting of a set of first elements representing the positions of the brightness change coordinates extracted from the data, and a second numerical sequence processing system for calculating a displacement of a second element of the measured object by performing arithmetic processing on a second numerical sequence consisting of a set of second elements representing the positions of the brightness change coordinates extracted from the data. [Effects of the Invention]

[0006] According to the displacement amount measuring device of one embodiment, it is possible to realize a displacement amount measuring device that can reduce the calculation load and detect the displacement amount of a measurement object at high speed. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing the overall configuration of a displacement measuring device according to a first embodiment; [Figure 2] FIG. 1 is a diagram showing an example of the configuration of a luminance change coordinate detection means included in a displacement amount measuring device according to a first embodiment; [Figure 3] FIG. 10 is a diagram showing another example of the configuration of the luminance change coordinate detection means included in the displacement amount measuring device according to the first embodiment; [Figure 4] FIG. 10 is a diagram showing an example of event data output by a luminance change coordinate detection means included in the displacement amount measuring device according to the first embodiment; [Figure 5] FIG. 1 is a diagram for explaining the principle of estimation of a displacement amount by a displacement amount estimation means provided in a displacement amount measuring device according to a first embodiment; [Figure 6] FIG. 1 is a diagram for explaining the principle of a method for estimating the displacement amount of a measurement object by a displacement amount estimating means according to an embodiment. [Figure 7]FIG. 10 is a diagram for explaining an example of a method for calculating the displacement of an object to be measured by a displacement amount estimation unit included in a displacement amount measuring device according to an embodiment; [Figure 8] A histogram showing the frequency distribution of a plurality of difference values ​​calculated by a displacement amount estimation means included in a displacement amount measuring device according to an embodiment. [Figure 9] FIG. 2 is a diagram showing an example of the functional configuration of a displacement amount estimation unit included in the displacement amount measuring device according to the embodiment; [Figure 10] 1 is a flowchart showing an example of a processing procedure performed by a displacement amount estimation unit included in a displacement amount measuring device according to an embodiment; [Figure 11] Graph showing an example of the amount of calculation by a displacement amount estimation unit included in a displacement amount measuring device according to an embodiment. [Figure 12] FIG. 10 is a diagram for explaining another example of a method for calculating the displacement of an object to be measured by the displacement estimation means included in the displacement measurement device according to an embodiment. [Figure 13] Graph showing another example of the amount of calculation by the displacement amount estimation means included in the displacement amount measuring device according to an embodiment. [Figure 14] FIG. 10 is a diagram showing another example of the functional configuration of the displacement amount estimation means included in the displacement amount measuring device according to the embodiment; [Figure 15] FIG. 10 is a diagram showing yet another example of the functional configuration of the displacement amount estimation means included in the displacement amount measuring device according to the embodiment; [Figure 16] 1 is a hardware configuration diagram of an information processing unit included in a displacement amount measuring device according to an embodiment; [Figure 17] 1 is a schematic diagram of a non-contact input device that is a first example of a displacement amount measuring device according to an embodiment; [Figure 18] 1 is a cross-sectional view of a non-contact input device that is a first example of a displacement amount measuring device according to an embodiment; [Figure 19] FIG. 1 is a schematic diagram of a tremor measurement device, which is a second example of a displacement measurement device according to an embodiment; [Figure 20] FIG. 10 is a cross-sectional view of a tremor measurement device, which is a second example of a displacement measurement device according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, an embodiment will be described with reference to the drawings.

[0009] [First embodiment] (Overall configuration of the displacement measuring device 100) Fig. 1 is a diagram showing the overall configuration of a displacement amount measuring device 100 according to the first embodiment. The displacement amount measuring device 100 shown in Fig. 1 is a device that can irradiate a coherent light onto a measurement object 10 (for example, a human hand), detect luminance change coordinates based on the light reflected from the measurement object 10, and measure minute displacement amounts of the measurement object 10 based on event data related to the detected luminance change coordinates.

[0010] The "brightness change coordinates" are pixels in the image sensor where a certain level of brightness change has occurred. The "event data" is data about pixels where a certain level of brightness change has occurred, including the time (T) when the brightness change occurred, the position (X, Y), and the polarity (P).

[0011] The minute displacement of the object to be measured 10 measured by the displacement measuring device 100 is output, for example, to an external device of the displacement measuring device 100, and is used in the external device for display to a user, control of an external controlled device, etc.

[0012] As shown in FIG. 1, the displacement measuring device 100 includes an irradiation means 110 (sometimes called a “light projecting means”), an interference image forming means 120, a luminance change coordinate detecting means 130, and an information processing unit 150.

[0013] The irradiation means 110 irradiates the object 10 under measurement with coherent light. It is preferable that the irradiation means 110 uses a laser light source with high coherence so that an interference image due to the light reflected by the object 10 under measurement can be formed on the light receiving surface of the luminance change coordinate detection means 130. As the irradiation means 110, for example, a laser diode (LD), a vertical cavity surface emitting laser (VCSEL), a small gas laser, a solid state laser, etc. can be used.

[0014] The interference image forming means 120 forms an interference image from the light reflected by the object 10 (i.e., coherent light reflected by the object 10). In this embodiment, the interference image forming means 120 is disposed on the optical path of the light reflected from the object 10, between the object 10 and the luminance change coordinate detecting means 130. The interference image forming means 120 has a function of adjusting the characteristics of the interference image received on the light receiving surface of the luminance change coordinate detecting means 130 so that the displacement amount of the object 10 can be appropriately acquired. For example, the interference image forming means 120 is configured to include so-called wavefront control elements such as lenses, apertures, phase shift elements, and spatial light modulators (SLMs).

[0015] As an example of an interference image formed by the interference image forming means 120, a speckle image is used, which is a random interference image caused by the roughness of the surface of the object under test 10. The speckle image reflects the wave properties of light, and changes the brightness distribution of the image extremely sensitively in response to the movement of the object under test 10. In other words, the speckle image has its sensitivity scaled to a level at which minute displacements of the object under test 10 can be detected on the light receiving surface of the brightness change coordinate detecting means 130.

[0016] The luminance change coordinate detecting means 130 receives the interference image formed by the interference image forming means 120 on the light receiving surface, and detects luminance change coordinates where a luminance change of a certain level or more has occurred based on the received interference image. The luminance change coordinate detecting means 130 then outputs event data related to the detected luminance change coordinates. An example configuration of the luminance change coordinate detecting means 130 will be described later using FIGS. 2 and 3.

[0017] The information processing unit 150 includes a displacement amount estimation unit 151 and a displacement estimated value output unit 152 .

[0018] The displacement amount estimation means 151 calculates an estimated value of the displacement amount of the object to be measured 10 in real space based on the event data output from the brightness change coordinate detection means 130 .

[0019] The displacement estimated value output means 152 outputs the estimated value of the displacement amount of the object to be measured 10 calculated by the displacement amount estimating means 151 .

[0020] Here, in the displacement amount measuring device 100 according to the first embodiment, the displacement amount estimation means 151 can calculate an estimated value of the displacement amount of the object to be measured 10 in real space by using two numerical sequence processing systems provided in parallel in terms of hardware for two numerical sequence of two elements (X coordinate and Y coordinate) that represent the position of the brightness change coordinates.

[0021] That is, the displacement amount estimation means 151 can perform, in parallel, the calculation of the X-axis displacement amount of the object to be measured 10 based on the numerical sequence of X coordinate values ​​by the first numerical sequence processing system P1, and the calculation of the Y-axis displacement amount of the object to be measured 10 based on the numerical sequence of Y coordinate values ​​by the second numerical sequence processing system P2. Note that "parallel" in this specification means that the calculations can be performed independently, and also includes the case where some of the calculations are performed at the same time.

[0022] As a result, the displacement measuring device 100 according to the first embodiment can reduce the calculation load and detect the displacement of the object to be measured 10 at high speed.

[0023] Each function of the information processing unit 150 can be realized by one or more processing circuits. Here, the term "processing circuit" in this specification includes a processor programmed to execute each function by software, such as a processor implemented by an electronic circuit, and devices such as an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and a conventional circuit module designed to execute each function described above.

[0024] (An example of the configuration of the luminance change coordinate detection means 130) FIG. 2 is a diagram showing an example of the configuration of the luminance change coordinate detecting means 130 included in the displacement amount measuring device 100 according to the first embodiment.

[0025] In the example shown in FIG. 2, the luminance change coordinate detection means 130 includes an event-based vision camera 131.

[0026] The event-based vision camera 131 is equipped with an event-based vision sensor. By receiving an interference image, the event-based vision sensor can instantly (i.e., in an extremely short time and at an extremely high speed) detect brightness change coordinates where a brightness change of a certain level or more has occurred in a two-dimensionally arranged pixel group, and output event data for the detected brightness change coordinates, including the time (T) when the brightness change occurred, the position (X, Y) where it occurred, and the polarity (P). This allows the event-based vision camera 131 to directly generate event data.

[0027] By using an event-based vision camera 131 as the brightness change coordinate detection means 130, the displacement measuring device 100 can quickly acquire sharply changing speckle images and reliably capture minute displacements of the object 10 to be measured.

[0028] (Another example of the configuration of the luminance change coordinate detection means 130) FIG. 3 is a diagram showing another example of the configuration of the luminance change coordinate detecting means 130 included in the displacement amount measuring device 100 according to the first embodiment.

[0029] In the example shown in FIG. 3, the luminance change coordinate detection means 130 comprises a frame camera 132, a luminance difference calculation means 133 between successive frames, and a luminance change coordinate extraction means 134.

[0030] The frame camera 132 captures a normal frame image in which an interference image is projected, and outputs the frame image. The consecutive frame luminance difference calculation means 133 calculates the luminance difference of each pixel in two consecutive frame images output from the frame camera 132. The luminance change coordinate extraction means 134 extracts, as luminance change coordinates, pixels for which the luminance change coordinate extraction means 134 calculates a luminance difference equal to or greater than a certain level. The luminance change coordinate extraction means 134 then outputs event data for the extracted luminance change coordinates, including the time (T) at which the luminance change occurred, the position (X, Y), and the polarity (P) of the luminance change.

[0031] (Example of event data output by the brightness change coordinate detection means 130) FIG. 4 is a diagram showing an example of event data output by the luminance change coordinate detecting means 130 included in the displacement amount measuring device 100 according to the first embodiment.

[0032] Figures 4(a) and 4(b) are diagrams showing examples of speckle images formed on the light receiving surface of the event-based vision sensor included in event-based vision camera 131. Note that Figure 4(a) shows speckle image 400A at time t. Figure 4(b) shows speckle image 400B at time t+Δt. Figure 4(c) is an example of event data output by event-based vision camera 131, which is event data 410 generated based on the speckle image shown in Figure 4(a) and the speckle image shown in Figure 4(b).

[0033] The event-based vision sensor of the event-based vision camera 131 is a photodetector that outputs data including the time of occurrence (T), location (X, Y), and polarity (P) of an event when a pixel (i.e., brightness change coordinate) whose brightness change exceeds a predetermined threshold is detected in a two-dimensionally arranged pixel group (i.e., when an event occurs). The polarity (P) can take two values: "1: increase" or "0: decrease."

[0034] For example, if speckle image 400A at time t shown in Figure 4(a) translates horizontally after Δt to speckle image 400B at time t+Δt shown in Figure 4(b), the polarity of the brightness change of the event-based vision sensor at time t+Δt will be spatially distributed as shown in event data 410 in Figure 4(c), with a decrease component 410A (lightly shaded area in the figure) where the brightness value has decreased by more than a certain value, and an increase component 410B (darker shaded area in the figure) where the brightness value has increased by more than a certain value.

[0035] In this case, the event-based vision sensor outputs a group of signal time-series data for all pixels in the increasing component 410B, including the time (T) of signal detection, pixel position (X, Y), and polarity (1: increase). The event-based vision sensor also outputs a group of signal time-series data for all pixels in the decreasing component 410A, including the time (T) of signal detection, pixel position (X, Y), and polarity (0: decrease). The event-based vision sensor does not output data for any pixels in other areas (unshaded areas in the figure) that do not fall into either the decreasing component 410A or the increasing component 410B. Therefore, the event data 410 output from the event-based vision sensor contains an extremely small amount of data compared to frame image data.

[0036] In this way, the event-based vision sensor is not restricted by the frame rate and can output speckle image shift information as event data at high speed compared to an image sensor that outputs frame image data.

[0037] For example, the sampling time for all event data within the sensor plane of an event-based vision sensor is approximately 1 to 200 μs, which is extremely fast compared to the frame rate of a normal video camera, etc. Therefore, the event-based vision sensor included in the brightness change coordinate detection means 130 can quickly and reliably detect the shift amount of the speckle image, which changes sensitively in response to the displacement of the object 10 to be measured.

[0038] (Principle of Estimation of Displacement Amount by Displacement Amount Estimation Means 151) FIG. 5 is a diagram for explaining the principle of estimation of the displacement amount by the displacement amount estimation means 151 provided in the displacement amount measuring device 100 according to the first embodiment.

[0039] 5(a) and 5(b) are examples of frame images based on event data output from the event-based vision camera 131. FIG. 5(a) shows a frame image 500A at time t. FIG. 5(b) shows a frame image 500B at time t+Δts. Note that frame images 500A and 500B only show increasing components whose luminance values ​​have increased by a certain value or more. FIG. 5(c) shows an example of a cross-correlation function calculated based on frame images 500A and 500B.

[0040] First, in this estimation principle, in order to obtain a frame image 500A as shown in FIG. 5(a) from the time series data of the event data output from the event-based vision camera 131, an accumulation time for calculating a unit frame is set, a two-dimensional matrix representing the image is prepared, and the number of times that a matrix number corresponding to a pixel position appears within the accumulation time is counted.

[0041] Next, as shown in Figure 5(b), this estimation principle counts the number of occurrences of row and column numbers that appear within the integration time, using the time of frame image 500A in Figure 5(a), for example, a time that is Δts away from the integration start time (t), as the starting point of integration.

[0042] The dotted lines in frame image 500B in FIG. 5(b) indicate the patterns in frame image 500A in FIG. 5(a), and these patterns are translated to positions shown by light shading in frame image 500B in FIG. 5(b).

[0043] Next, the present estimation principle calculates the cross-correlation function (see FIG. 5(c)) between the frame image 500A and the frame image 500B.

[0044] As shown in Fig. 5(c), when the variables of the correlation function, i.e., the displacement amount, are taken as the ΔX axis and the ΔY axis, the peak value of the cross-correlation function is obtained at the distance and position (pixel displacement amount on the image) corresponding to the translation amount of the speckle pattern. For example, this estimation principle can calculate the cross-correlation function shown in Fig. 5(c) by shifting either frame image 500A or 500B in the X-axis direction and Y-axis direction and integrating the overlapping area of ​​the images.

[0045] In addition, this estimation principle can also use a method (Wiener-Khintchine theorem) in which the cross-correlation function is calculated by Fourier transforming frame images 500A and 500B, multiplying one by the complex conjugate of the other, and then performing an inverse Fourier transform.

[0046] (Principle of the displacement amount estimation method by the displacement amount estimation means 151) FIG. 6 is a diagram for explaining the principle of a method for estimating the displacement amount of the object to be measured 10 by the displacement amount estimating means 151 according to one embodiment.

[0047] Fig. 6(a) is a diagram showing an optical system included in the displacement amount measuring device 100 according to one embodiment. Fig. 6(b) is a diagram showing an example of an event data group output from the event-based vision camera 131 included in the displacement amount measuring device 100 according to one embodiment. Fig. 6(c) is a diagram showing images of the event data groups at two different times.

[0048] As shown in Figure 6(a), the displacement measuring device 100 irradiates coherent light from the irradiation means 110 onto the rough surface 10A of the object to be measured 10, and receives the reflected light on the light receiving surface of the brightness change coordinate detection means 130, thereby measuring the speckle image formed on the light receiving surface of the event-based vision camera 131.

[0049] 6(a), when the rough surface 10A is displaced, the speckle image on the light receiving surface of the luminance change coordinate detecting means 130 also translates in the same direction. Furthermore, the ratio between the amount of displacement of the rough surface 10A and the amount of translation of the speckle image on the light receiving surface of the luminance change coordinate detecting means 130 is constant under the same conditions. Therefore, the displacement amount measuring device 100 can estimate the displacement of the object 10 based on the translation of the speckle image on the light receiving surface of the luminance change coordinate detecting means 130.

[0050] An event data group 600 shown in Fig. 6(b) is an event data group including 100 consecutive event data in chronological order that were acquired at a time before the displacement of the rough surface 10A. An event data group 601 shown in Fig. 6(b) is an event data group including 100 consecutive event data in chronological order that were acquired at a time after the displacement of the rough surface 10A. As shown in Fig. 6(b), each event data constituting the event data groups 600 and 601 includes the time, coordinates, and polarity at which a luminance change occurred.

[0051] Therefore, when 100 pieces of event data included in the event data group 600 shown in FIG. 6(b) are added together, a plurality of speckle images 610 shown in FIG. 6(c) are obtained.

[0052] Furthermore, when 100 pieces of event data included in the event data group 601 shown in FIG. 6(b) are summed, a plurality of speckle images 610' shown in FIG. 6(c) are obtained.

[0053] That is, the plurality of speckle images 610 translate into the plurality of speckle images 610' in accordance with the displacement of rough surface 10A. Therefore, the difference between the plurality of speckle images 610' and the plurality of speckle images 610, that is, the amount of displacement of rough surface 10A, can be estimated.

[0054] Since the time between event data groups 601 and 601 is extremely short, it is safe to assume that rough surface 10A and the plurality of speckle images 610 are moving at a constant speed. Therefore, the pattern of the plurality of speckle images 610 and the pattern of the plurality of speckle images 610' are substantially identical.

[0055] (An example of a method for calculating the amount of displacement by the displacement amount estimation means 151) FIG. 7 is a diagram for explaining an example of a method for calculating the displacement of the object to be measured 10 by the displacement amount estimation means 151 provided in the displacement amount measuring device 100 according to one embodiment.

[0056] In FIG. 7, a method for calculating the displacement amount of the object under test 10 will be described using five luminance change coordinates included in the event data group as representatives.

[0057] 7(a) to 7(c) are brightness change coordinates detected at a time before the displacement of the rough surface 10A. Brightness change coordinates 700' shown in Fig. 7(a) to 7(c) are brightness change coordinates detected at a time after the displacement of the rough surface 10A, and are obtained by translating the brightness change coordinates 700.

[0058] First, as shown in FIG. 7(a), the displacement estimation means 151 focuses on the first brightness change coordinate 700 in the time series and calculates the difference values ​​of the coordinate values ​​between the first brightness change coordinate 700 and each of the five brightness change coordinates 700′.

[0059] Next, as shown in FIG. 7(b), the displacement estimation means 151 focuses on the second brightness change coordinate 700 in the time series and calculates the difference values ​​of the coordinate values ​​between the second brightness change coordinate 700 and each of the five brightness change coordinates 700′.

[0060] Similarly, the displacement estimation means 151 focuses on the third brightness change coordinate 700 in the time series, and calculates the difference values ​​between the third brightness change coordinate 700 and each of the five brightness change coordinates 700'.

[0061] Similarly, the displacement estimation means 151 focuses on the fourth brightness change coordinate 700 in the time series, and calculates the difference values ​​between the fourth brightness change coordinate 700 and each of the five brightness change coordinates 700'.

[0062] Finally, as shown in FIG. 7(c), the displacement estimation means 151 focuses on the fifth brightness change coordinate 700 in the time series and calculates the difference value between the coordinate value of the fifth brightness change coordinate 700 and each of the five brightness change coordinates 700′.

[0063] That is, the displacement amount estimation means 151 calculates the difference value of the coordinate value between all brightness change coordinates 700 included in the event data group before the displacement of the rough surface 10A and each of all brightness change coordinates 700' included in the event data group after the displacement of the rough surface 10A.

[0064] Therefore, for example, if the event data group before the displacement of the rough surface 10A and the event data group after the displacement of the rough surface 10A each contain 100 event data, the displacement amount estimation means 151 calculates 100 x 100 = 10,000 difference values.

[0065] Here, when focusing on one brightness change coordinate 700 included in the event data group before the displacement, there is always one difference value (Δx, Δy) in the same direction and at the same distance as the translation of the entire speckle among the calculated difference values. This also applies to all brightness change coordinates 700.

[0066] Therefore, among the difference values ​​calculated by the displacement amount estimation means 151, there will ultimately be difference values ​​(Δx, Δy) in the same direction and at the same distance as the translation of the entire speckle, the number of which is the same as the number of event data included in the event data group before the displacement.

[0067] Therefore, when the frequency distribution of the multiple difference values ​​calculated by the displacement amount estimation means 151 is plotted as a histogram, the histogram has a peak at a difference value (Δx, Δy) in the same direction and at the same distance as the translation of the entire speckle.

[0068] (Frequency distribution of multiple difference values ​​calculated by the displacement amount estimation means 151) FIG. 8 is a histogram showing the frequency distribution of a plurality of difference values ​​calculated by the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to one embodiment.

[0069] The histogram shown in FIG. 8 represents the frequency distribution of multiple difference values ​​calculated by the displacement estimation means 151 using the method described in FIG. 7, with the horizontal axis representing the difference value of the coordinate value (X coordinate or Y coordinate) and the vertical axis representing the frequency.

[0070] As shown in Fig. 8, a histogram representing the frequency distribution of a plurality of difference values ​​has a peak at a certain difference value. This peak difference value is equivalent to the actual translation amount (actual movement amount) of the speckle image.

[0071] From this, the displacement amount estimation means 151 can identify the most frequent value among the multiple difference values ​​as the actual translation amount of the speckle image, and can estimate the displacement amount of the rough surface 10A of the object to be measured 10 based on the most frequent value.

[0072] In this way, the displacement amount estimation means 151 can calculate the translation amount of the speckle image by directly calculating the difference between the numerical sequences without generating two speckle images by integrating two event data groups respectively, and therefore can quickly calculate the displacement amount of the object to be measured 10 with reduced calculation load.

[0073] (Functional configuration of the displacement amount estimation means 151) FIG. 9 is a diagram showing an example of the functional configuration of the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to one embodiment.

[0074] As shown in FIG. 9, the displacement estimation means 151 includes an event data group generation means 171 and an element-specific numeric sequence generation means 172.

[0075] The event data group generating means 171 acquires a predetermined number of event data output from the brightness change coordinate detecting means 130, and generates an event data group including the predetermined number of event data.

[0076] The element-specific numeric sequence generating means 172 generates an element-specific numeric sequence in the event data group generated by the event data group generating means 171. Specifically, the element-specific numeric sequence generating means 172 generates a first numeric sequence consisting of a set of X coordinates (an example of a "first element") and a second numeric sequence consisting of a set of Y coordinates (an example of a "second element").

[0077] The displacement estimation means 151 also includes a first number sequence processing system P1 and a second number sequence processing system P2.

[0078] The first numeric sequence processing system P1 calculates the displacement of the X coordinate of the object under test 10 by performing arithmetic processing on a first numeric sequence consisting of a set of X coordinates (an example of a "first element") representing the positions of the luminance change coordinates extracted from the event data.

[0079] The second numeric sequence processing system P2 calculates the displacement of the Y coordinate of the object to be measured 10 by performing arithmetic processing on a second numeric sequence consisting of a set of Y coordinates (an example of a "second element") representing the position of the brightness change coordinate extracted from the event data.

[0080] Each of the first number sequence processing system P1 and the second number sequence processing system P2 has a number sequence correcting means 173, an operation combination selecting means 174, and a displacement amount deriving means 175.

[0081] The numeric sequence correction means 173 performs a predetermined correction on the first numeric sequence or the second numeric sequence. The predetermined correction is, for example, a process of extracting only the brightness change coordinates of the event data having either positive or negative polarity, a sorting process, or the like.

[0082] The operation combination selection means 174 selects a combination of brightness change coordinates to be used for operation for the first numeric sequence or the second numeric sequence corrected by the numeric sequence correction means 173. Specifically, the operation combination selection means 174 selects a combination of brightness change coordinates included in one event data group and brightness change coordinates included in the other event data group (for example, a brute force combination, a combination of the same descending order, etc.).

[0083] The displacement amount deriving means 175 calculates the difference value of the coordinate values ​​for all combinations of brightness change coordinates selected by the calculation combination selecting means 174. Then, the displacement amount deriving means 175 specifies the most frequent value among the calculated multiple difference values ​​as the translation amount of the actual speckle image in the X-axis or Y-axis, and estimates the displacement amount of the object under test 10 in the X-axis or Y-axis based on the most frequent value. Furthermore, the displacement amount deriving means 175 outputs the estimated displacement amount of the object under test 10 in the X-axis or Y-axis to the displacement estimated value output means 152.

[0084] The displacement amount estimation means 151 may not have the numerical sequence correction means 173 and the calculation combination selection means 174. That is, the displacement amount estimation means 151 may not correct the numerical sequence and may not select a combination of brightness change coordinates to be calculated. In this case, the displacement amount estimation means 151 may automatically select a "brute force combination."

[0085] (An example of a processing procedure by the displacement amount estimation means 151) FIG. 10 is a flowchart showing an example of a processing procedure by the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to an embodiment.

[0086] First, the event data group generating means 171 acquires the event data output from the luminance change coordinate detecting means 130 (step S101). Next, the event data group generating means 171 stores the event data acquired in step S101 in a memory included in the displacement amount measuring device 100 (step S102).

[0087] Then, by repeatedly executing steps S101 and S102, when a predetermined number (for example, 100) of event data are stored in memory, the event data group generation means 171 generates an event data group from the predetermined number of event data (step S103).

[0088] Moreover, the event data group generating means 171 executes steps S101 to S103 twice to generate event data groups at two different times.

[0089] Next, the element-specific numeric sequence generating means 172 generates a first numeric sequence consisting of a set of X coordinates and a second numeric sequence consisting of a set of Y coordinates for each of the two generated event data groups (step S104).

[0090] Next, in the first numeric sequence processing system P1, the numeric sequence correcting means 173 performs a predetermined correction (e.g., classification by polarity, sorting, etc.) on the first numeric sequence (step S105). Furthermore, the calculation combination selecting means 174 selects a combination of brightness change coordinates to be calculated for the first numeric sequence corrected in step S105 (step S106). Then, the displacement amount deriving means 175 calculates the difference values ​​of the coordinate values ​​for all the combinations of brightness change coordinates selected in step S106, identifies the most frequent value among the calculated multiple difference values ​​as the translation amount of the actual speckle image about the X axis, and estimates the displacement amount of the object under test 10 about the X axis based on the most frequent value (step S107).

[0091] In parallel with steps S105 to S107, in the second numeric sequence processing system P2, the numeric sequence correcting means 173 performs a predetermined correction (e.g., classification by polarity, sorting, etc.) on the second numeric sequence (step S108). Furthermore, the calculation combination selecting means 174 selects a combination of brightness change coordinates to be calculated for the second numeric sequence corrected in step S108 (step S109). Then, the displacement amount deriving means 175 calculates difference values ​​of coordinate values ​​for all combinations of brightness change coordinates selected in step S109, identifies the most frequent value among the calculated difference values ​​as the amount of translation of the actual speckle image along the Y axis, and estimates the amount of displacement of the object under test 10 along the Y axis based on the most frequent value (step S110).

[0092] Furthermore, the displacement amount derivation means 175 outputs the X-axis displacement amount of the object to be measured 10 estimated in step S107 and the Y-axis displacement amount of the object to be measured 10 estimated in step S110 to the displacement estimation value output means 152 (step S111).

[0093] Thereafter, the displacement amount estimation means 151 ends the series of processes shown in Fig. 10. Note that the displacement amount estimation means 151 can continue to estimate the displacement amount of the object to be measured 10 at high speed by repeatedly executing the series of processes shown in Fig. 10.

[0094] (Example of the amount of calculation by the displacement amount estimation means 151) FIG. 11 is a graph showing an example of the amount of calculation by the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to one embodiment.

[0095] The graph shown in FIG. 11 shows the amount of calculation required by the displacement amount measuring device 100 when the event-based vision camera 131 having an image element of 320×240 px outputs 10,000 event data per second.

[0096] 11, the horizontal axis represents the number of event data groups per second, which represents the velocity resolution of the displacement. The larger the value of the number of event data groups per second, the more quickly the displacement of the object under test 10 can be tracked. If the number of event data included in an event data group is n, the number of event data groups per second is the value obtained by dividing the number of event data output in one second by n.

[0097] The graph shown in Fig. 11 includes, as legends, a "brute force method" indicated by a solid triangular line and an "image correlation method" indicated by a dotted circle line. The "brute force method" is a method used in the displacement measuring device 100 according to one embodiment. On the other hand, the "image correlation method" is a method used in conventional displacement measuring devices.

[0098] The "brute force method" is a method in which difference values ​​are calculated for all combinations of all brightness change coordinates included in one event data group and all brightness change coordinates included in the other event data group, and the most frequent value among the calculated difference values ​​is calculated as the displacement amount of the object to be measured 10.

[0099] The "image correlation method" is a method for determining the amount of displacement of the object under test 10 from the correlation between two images generated from two event data groups.

[0100] In the "brute force method," it is necessary to calculate the difference value of all combinations, and the amount of calculation required to calculate the difference value by brute force is O(n 2 ), the computational complexity for finding the frequency distribution is O(n 2 ), so the total computational complexity is O(n 2 ) Therefore, in the "brute force method," the amount of calculation required to find the displacement of the object to be measured 10 can be expressed by the following formula (1).

[0101]

number

[0102] For this reason, in the "brute force method," the amount of calculation per run is proportional to the number n of event data included in the event data group. Also, the number of event data groups per second is inversely proportional to the number n of event data included in the event data group. Therefore, the amount of calculation per second for each event data group is inversely proportional.

[0103] In the "image correlation method," two images must be Fourier transformed, a composite image must be generated, and then an inverse Fourier transform must be performed. The amount of calculation required for the Fourier transform and inverse Fourier transform can be expressed as NlogN, where N is the number of pixels. Furthermore, the amount of calculation required to generate a composite image is N. Therefore, in the "image correlation method," the amount of calculation required to find the displacement of the object 10 to be measured can be expressed by the following formula (2).

[0104]

number

[0105] For this reason, in the "image correlation method," the amount of calculation per run does not depend on the number n of event data included in the event data group. Therefore, the amount of calculation per second for the event data group is roughly proportional.

[0106] According to the graph shown in FIG. 11, in a situation where the number of event data groups per second exceeds approximately 275 (a situation where the object to be measured 10 is displaced at high speed), the "brute force method" used in the displacement amount measuring device 100 according to one embodiment can estimate the displacement amount of the object to be measured 10 with less calculation effort than the "image correlation method" used in conventional displacement amount measuring devices.

[0107] (Another example of a method for calculating the amount of displacement by the displacement amount estimation means 151) FIG. 12 is a diagram for explaining another example of a method for calculating the displacement of the object to be measured 10 by the displacement amount estimation means 151 provided in the displacement amount measuring device 100 according to an embodiment.

[0108] In FIG. 12, a method for calculating the displacement amount of the object to be measured 10 will be described using five luminance change coordinates included in the event data group as representatives.

[0109] 12(a) and 12(b) are brightness change coordinates detected at a time before the displacement of rough surface 10A. Brightness change coordinates 700' shown in Fig. 12(a) and 12(b) are brightness change coordinates detected at a time after the displacement of rough surface 10A, and are obtained by translating brightness change coordinates 700.

[0110] The numbers assigned to the brightness change coordinates 700, 700' indicate the order when the coordinate values ​​on the Y axis are sorted in descending order. Also, Fig. 12(b) shows the brightness change coordinates 700, 700' of Fig. 12(a) arranged on the same straight line (on the Y axis) in descending order of the coordinate values ​​on the Y axis.

[0111] As a "sorting method," the displacement amount estimation means 151 calculates, for each of the five brightness change coordinates 700, the difference value between the brightness change coordinate 700 and the brightness change coordinate 700' having the same number.

[0112] For example, for a brightness change coordinate 700 to which "1" is assigned, the displacement amount estimation means 151 calculates the difference value between the brightness change coordinate 700 and a brightness change coordinate 700' to which "1" is assigned.

[0113] Furthermore, for example, the displacement amount estimation means 151 calculates the difference value between the brightness change coordinate 700 to which "2" is assigned and the brightness change coordinate 700' to which "2" is assigned.

[0114] Similarly, for each brightness change coordinate 700 assigned with another number, the displacement amount estimation means 151 calculates the difference value between the brightness change coordinate 700 and the brightness change coordinate 700' assigned with the same number.

[0115] This allows the displacement amount estimation means 151 to calculate only the difference between each of the plurality of brightness change coordinates 700 and the brightness change coordinate 700' assigned the same number (i.e., only the difference value equal to the total translation amount). Therefore, the displacement amount estimation means 151 can reduce the amount of calculation required for calculating the difference value compared to the "brute force method" shown in FIG.

[0116] When the displacement estimation means 151 uses the "sorting method," it may calculate, for each of a plurality of brightness change coordinates 700, not only the difference value between the brightness change coordinate 700' assigned with the same number and a single brightness change coordinate 700', but also the difference value between the brightness change coordinate 700' and a plurality of brightness change coordinates 700' assigned with numbers around the same number.

[0117] For example, for a brightness change coordinate 700 assigned with "2", the displacement amount estimation means 151 may calculate not only the difference value between the brightness change coordinate 700' assigned with "2", but also the difference value between the brightness change coordinate 700' assigned with "1", and the difference value between the brightness change coordinate 700' assigned with "3".

[0118] As a result, even if there is a discrepancy in numbers between the brightness change coordinates 700 and the brightness change coordinates 700' due to noise, overlapping of event data, etc., the displacement amount estimation means 151 can calculate the difference value between the actually corresponding brightness change coordinates 700 and the brightness change coordinates 700'.

[0119] (Example of the amount of calculation by the displacement amount estimation means 151) FIG. 13 is a graph showing another example of the amount of calculation by the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to an embodiment.

[0120] The graph shown in FIG. 13 shows the amount of calculation required by the displacement amount measuring device 100 when 10,000 items of event data are output per second in an event-based vision camera 131 equipped with an image element of 320×240 px.

[0121] 13 includes, as legends, a "brute force method" indicated by a solid triangular line, an "image correlation method" indicated by a dotted circle line, and a "sorting method" indicated by a dashed square line. Note that the "sorting method" is another method used in the displacement measuring device 100 according to one embodiment.

[0122] Also, in this "sorting method," for each calculation source brightness change coordinate (corresponding to brightness change coordinate 700 in FIG. 12), the range of the calculation partner brightness change coordinate (corresponding to brightness change coordinate 700' in FIG. 12) is set to "same number ±3," that is, the number of calculation partner brightness change coordinates (number of surrounding areas) is set to "7."

[0123] In the "sorting method," nlog(n) computations are required to sort the sequence of event data groups, and 2nlog(n) computations are required to perform this calculation on two sequences.

[0124] In addition, in this case, in the "sorting method," the number of event data included in the event data group is n, and the number of brightness change coordinates (number of surrounding areas) to be calculated is "7," so a calculation amount of 7n is required.

[0125] Furthermore, the "sorting method" requires O(n log n) computational effort to sort the sequence of event data groups, O(n) to calculate coordinate differences, and O(n) to calculate the frequency distribution, resulting in an overall computational effort of O(n log n).

[0126] Therefore, in the "sorting method," the amount of calculation required to find the amount of displacement of the object under test 10 can be expressed by the following formula (3).

[0127]

number

[0128] For this reason, in the "sorting method," the amount of calculation per run is proportional to nlog(n). Also, the number of event data groups per second is inversely proportional to the number of event data, n, contained in the event data group. Therefore, the amount of calculation per second for the event data group is proportional to log(n), and when n is large, the amount of calculation is almost constant.

[0129] According to the graph shown in FIG. 13, it can be seen that the "sorting method" can estimate the displacement amount of the object to be measured 10 with a smaller amount of calculation than the "brute force method."

[0130] (Another example of the functional configuration of the displacement amount estimation means 151) FIG. 14 is a diagram showing another example of the functional configuration of the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to an embodiment.

[0131] 14, an exposure area 131B is set for a light receiving element 131A of an event-based vision camera 131 provided in a brightness change coordinate detection means 130. This exposure area 131B is scanned in the X-axis direction over time. As a result, the X-coordinate values ​​of the event data output from the event-based vision camera 131 are periodically sorted in advance.

[0132] Therefore, the displacement amount estimation means 151 only needs to sort the second numeric sequence related to the Y axis, and the numeric sequence correction means 173 of the first numeric sequence processing system P1 is not required. Therefore, the displacement amount measuring device 100 shown in FIG. 14 can further reduce the amount of calculation processing of the displacement amount estimation means 151.

[0133] (Yet another example of the functional configuration of the displacement amount estimation means 151) FIG. 15 is a diagram showing yet another example of the functional configuration of the displacement amount estimation means 151 included in the displacement amount measuring device 100 according to an embodiment.

[0134] The displacement measuring device 100 shown in Fig. 15 differs from the displacement measuring device 100 shown in Fig. 9 in that each of the first numeric sequence processing system P1 and the second numeric sequence processing system P2 has a frequency distribution array generating means 176 instead of the numeric sequence correcting means 173. The frequency distribution array generating means 176 generates two frequency distribution arrays from two event data groups at different times.

[0135] 15 differs from the displacement measuring device 100 shown in FIG. 9 in that in each of the first number sequence processing system P1 and the second number sequence processing system P2, the displacement amount derivation means 175 calculates the displacement amount of the object to be measured 10 by using a "convolution calculation method" instead of a "brute force method."

[0136] 15 differs from the displacement amount measuring device 100 shown in FIG. 9 in that the first number sequence processing system P1 and the second number sequence processing system P2 do not have an operation combination selection means 174.

[0137] Hereinafter, a method for calculating the displacement of the object to be measured 10 using the "convolution calculation method" by the displacement amount derivation means 175 provided in the displacement amount measuring device 100 shown in FIG. 15 will be described, focusing on the X-axis coordinate element of the event data group.

[0138] In the following description, the number of sensors of the event camera in the X-axis direction is denoted as M, a group of event data that is early in time series is denoted as A, and a group of event data that is late in time series is denoted as B.

[0139] Event data group A includes N pieces of event data, and the X coordinates of the N pieces of event data are represented as Ax0, Ax1, Ax2, . . . AxN-1, respectively.

[0140] Furthermore, the event data group B includes N pieces of event data, and the X coordinates of the N pieces of event data are represented as Bx0, Bx1, Bx2, . . . BxN-1, respectively.

[0141] Furthermore, Axi and Bxi (i=0, 1, . . . , N-1) are integers in the range (0 to M-1) that the X coordinate can have.

[0142] Here, s (a sequence in which the number of events in event data group A where Ax is M-1-i is defined as s[i]) and t (a sequence in which the number of events in event data group B where Bx is i is defined as t[i]) are set as sequences that focus on how many identical coordinates there are among the coordinate information Ax and Bx of event data A and B. From these sequences s and t, an array d can be defined using the following formula (4).

[0143]

number

[0144] Note that d[k] is equal to the number of pairs of integers (i, j) (0≦i, j≦N−1) that satisfy Bxj−Ax_i=k−(M−1).

[0145] Transforming the right side of the above formula (4) gives the following formula (5), which can be expressed in the form of a convolution.

[0146]

number

[0147] From this, if the arrays obtained by performing the discrete Fourier transform on arrays s, t, and d are S, T, and D respectively, array D is D[k]=S[k]·T[k] (k=0,1,…,2M-2) Furthermore, by performing an inverse discrete Fourier transform on D (first array), d (second array) can be obtained. Since d indicates the frequency of the differential coordinates, the amount of translation of the speckle can be estimated by extracting the most frequent value of d.

[0148] In addition, since the "convolution calculation method" uses a discrete Fourier transform to find the frequency of differences between sequences, it is preferable that each of the first numeric sequence processing system P1 and the second numeric sequence processing system P2 is equipped with an FPGA, GPU, etc. that can perform advanced calculation processing.

[0149] (Hardware configuration of information processing unit 150) Fig. 16 is a hardware configuration diagram of the information processing unit 150 included in the displacement amount measuring device 100 according to one embodiment. Fig. 16 shows an example of the hardware configuration of the information processing unit 150 when the information processing unit 150 is realized by a personal computer.

[0150] As shown in FIG. 16, the information processing unit 150 is constructed by a computer and includes a CPU 201A, a CPU 201B, a ROM 202, a RAM 203, an HD 204, an HDD (Hard Disk Drive) controller 205, a display 206, an external device connection I / F (Interface) 208, a network I / F 209, a data bus 210, a keyboard 211, a pointing device 212, a DVD-RW (Digital Versatile Disk Rewritable) drive 214, and a media I / F 216.

[0151] Of these, CPU 201A and CPU 201B control the overall operation of the information processing unit 150. ROM 202 stores programs used to drive CPU 201, such as IPL. RAM 203 is used as a work area for CPU 201. HD 204 stores various data, such as programs. HDD controller 205 controls reading and writing of various data from and to HD 204 under the control of CPU 201. Display 206 displays various information, such as a cursor, menu, window, text, or image. External device connection I / F 208 is an interface for connecting various external devices. In this case, external devices include, for example, USB (Universal Serial Bus) memory and a printer. Network I / F 209 is an interface for data communication using a communication network. Data bus 210 is an address bus, data bus, or the like for electrically connecting each component, such as CPU 201A and CPU 201B, shown in FIG. 16.

[0152] The keyboard 211 is a type of input means having multiple keys for inputting characters, numbers, various instructions, etc. The pointing device 212 is a type of input means for selecting and executing various instructions, selecting a processing target, moving a cursor, etc. The DVD-RW drive 214 controls reading and writing of various data from and to a DVD-RW 213, which is an example of a removable recording medium. Note that this is not limited to a DVD-RW, and may be a DVD-R, etc. The media I / F 216 controls reading and writing (storing) of data from and to a recording medium 215, such as a flash memory.

[0153] As described above, the information processing unit 150 has two CPUs (CPU 201A and CPU 201B). For example, the CPU 201A executes processing of a first number sequence processing system P1. Furthermore, for example, the CPU 201B executes processing of a second number sequence processing system P2. The CPU 201A and CPU 201B can execute processing in parallel with each other. This allows the information processing unit 150 to execute, in parallel, the arithmetic processing of a first number sequence by the CPU 201A (first number sequence processing system P1) and the second number sequence processing system by the CPU 201B (second number sequence processing system P2).

[0154] The first and second numeric sequence processing systems P1 and P2 may be any combination of hardware that can execute processing in parallel with each other, and are not limited to a combination of two CPUs, but may also be a combination of two arithmetic circuits, a combination of two computers, etc.

[0155] (First Example) Fig. 17 is a schematic diagram of a non-contact input device 1100 which is a first example of the displacement amount measuring device 100 according to an embodiment. Fig. 18 is a cross-sectional configuration diagram of the non-contact input device 1100 which is a first example of the displacement amount measuring device 100 according to an embodiment.

[0156] 17 and 18, a non-contact input device 1100 includes a housing 1101, an image display unit 1102, an imaging plate 1103, an optical window 1104, a non-contact input identification unit 1105, and a displacement amount measuring device 100. The displacement amount measuring device 100 included in the non-contact input device 1100 can be the displacement amount measuring device 100 according to an embodiment. Also, in FIGS. 17 and 18, the interference image forming unit 120 included in the displacement amount measuring device 100 is not shown.

[0157] In the non-contact input device 1100, the irradiation means 110 provided in the displacement amount measuring device 100 irradiates coherent light as a sheet light toward the upper and front of the housing 1101 (near the virtual image formed by the image display means 1102 and the imaging plate 1103). When the object 10 to be measured (the operator's finger) crosses the sheet light in response to a non-contact operation of the object 10 to the virtual image, the reflected light of the sheet light by the object 10 to be measured is incident as an interference image on the luminance change coordinate detection means 130 provided in the displacement amount measuring device 100 within the housing 1101 through the optical window 1104.

[0158] As a result, the information processing unit 150 (not shown) provided in the displacement measuring device 100 can detect the minute displacement of the object to be measured 10 and output information indicating the detected minute displacement of the object to be measured 10 to the non-contact input identification means 1105.

[0159] The non-contact input identification means 1105 can detect non-contact operations (e.g., finger pressing, handwriting, swiping, etc.) by the object to be measured 10 with high accuracy based on information indicating the minute displacement output from the displacement measuring device 100, and output the detection results to the operated device (not shown) or provide feedback to the operator.

[0160] In order to improve operability, the non-contact input device 1100 can use an imaging plate 1103 to form a virtual image from the image or video information displayed on the image display means 1102, and display the virtual image above and in front of the housing 1101. As shown in Fig. 18, the imaging plate 1103 is a member having light transmission and deflection properties, and can be realized by a laminated reflective structure.

[0161] The non-contact input device 1100 is equipped with a displacement amount measuring device 100 according to one embodiment, and the displacement amount measuring device 100 can quickly and reliably capture minute movements of the non-contact operation of the object to be measured 10 (the operator's finger), i.e., can detect the non-contact operation of the object to be measured 10 (the operator's finger) with high accuracy.

[0162] (Second Example) Fig. 19 is a schematic diagram of a tremor measuring device 1200 which is a second example of the displacement amount measuring device 100 according to one embodiment. Fig. 20 is a cross-sectional configuration diagram of the tremor measuring device 1200 which is a second example of the displacement amount measuring device 100 according to one embodiment.

[0163] 19 and 20, the tremor measuring device 1200 is an example of a "biological micromotion measuring device" and includes a housing 1201, a cylindrical lens 1202, a folding mirror 1203, an optical window 1204, a support base 1205, a display device 1206, and a displacement amount measuring device 100. The displacement amount measuring device 100 included in the tremor measuring device 1200 can be the displacement amount measuring device 100 according to one embodiment. In addition, in FIGS. 19 and 20, the interference image forming means 120 included in the displacement amount measuring device 100 is not shown.

[0164] The tremor measuring device 1200 shown in FIGS. 19 and 20 is a device capable of detecting small vibrations (e.g., tremors) of a living body, which is the object under test 10. Tremor is an involuntary movement that occurs when muscles contract and relax repeatedly, and a typical example is hand tremors. Tremor can be caused by, for example, stress, anxiety, fatigue, hyperthyroidism, alcohol withdrawal symptoms, etc. Furthermore, resting tremor is considered to be one of the main symptoms of Parkinson's disease.

[0165] Tremor measurement has traditionally been performed using myoelectric potential measurement or an acceleration sensor. The tremor measurement device 1200 shown in Figures 19 and 20 uses a displacement measurement device 100 to capture micro-vibrations of the object to be measured 10 at the micrometer level, making it possible to measure tremor with high accuracy in a non-contact environment.

[0166] As shown in Fig. 19, tremor measurement using tremor measurement device 1200 is performed by setting the angle from the elbow to the forearm at 45° with respect to a horizontal support base 1205. Tremor measurement device 1200 irradiates the back of the hand with coherent light from irradiation means 110, and the coherent light reflected by the back of the hand is incident on luminance change coordinate detection means 130 as an interference image.

[0167] This allows the information processing unit 150 included in the displacement measuring device 100 to detect minute displacements of the object 10, i.e., to measure with high accuracy the tremor of the object 10. The tremor data measured by the displacement measuring device 100 can be used to understand a person's condition or as medical data by performing frequency analysis or the like.

[0168] Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to these embodiments, and various modifications and changes are possible within the scope of the gist of the present invention described in the claims.

[0169] Note that each function of the "displacement amount measuring device" may be realized by a "displacement amount measuring system." In this case, the "displacement amount measuring system" may be physically realized by one device or may be physically realized by multiple devices.

[0170] Furthermore, the present invention is not limited to application to "biological micromotion measuring devices" and "non-contact input devices." For example, the present invention can also be applied to game machines, input / output devices, etc. Furthermore, the present invention is not limited to devices that utilize minute detection, but can also be applied to devices that eliminate minute movement errors. [Explanation of symbols]

[0171] 10 Object to be measured 10A Rough surface 100 Displacement measuring device 110 Irradiation means 120 Interference image forming means 130 Luminance change coordinate detection means 131 Event-based Vision Camera 131A Photodetector 131B Exposure area 132 frame camera 133 Luminance difference calculation means between consecutive frames 134 Luminance change coordinate extraction means 150 Information Processing Department 151 Displacement estimation method 152 Displacement estimation value output means 171 Event data group generation means 172 Element-specific numeric sequence generator 173 Numerical sequence correction means 174 Operation combination selection means 175 Displacement calculation means 176 Frequency distribution array generation means 400A, 400B speckle images 410 Event Data 410A Decrease component 410B Increased Component 500A, 500B frame images 600,601 Event data set 610,610' Speckle image 700,700' Brightness change coordinates 1100 Non-contact input device 1101 Case 1102 Image display means 1103 Imaging plate 1104 Optical window 1105 Non-contact input identification means 1200 Tremor measurement device (biological microtremor measurement device) 1201 Case 1202 Cylindrical Lens 1203 Folding Mirror 1204 Optical window 1205 Support stand 1206 Display Device P1 First numerical sequence processing system P2 Second numeric sequence processing system [Prior art documents] [Non-patent literature]

[0172] [Non-Patent Document 1] Zhou Ge,Yizhao Gao,Hayden K.-h. So,Edmund Y. Lam,"Event-based laser speckle correlation for micro motion estimation",Optics Letters 46 (2021) 3885-3888

Claims

1. an irradiation means for irradiating the object to be measured with coherent light; a luminance change coordinate detecting means for detecting a luminance change coordinate where a luminance change occurs based on the light reflected by the object to be measured, and outputting data relating to the luminance change coordinate; a displacement amount estimation means for estimating a displacement amount of the object to be measured based on data relating to the luminance change coordinates output from the luminance change coordinate detection means; Equipped with The displacement amount estimation means a first numerical sequence processing system that calculates the displacement of the first element of the object to be measured by performing arithmetic processing on a first numerical sequence consisting of a set of first elements that represent positions of the luminance change coordinates extracted from the data; a second numerical sequence processing system that performs arithmetic processing of a second numerical sequence consisting of a set of second elements that represent positions of the luminance change coordinates extracted from the data, thereby calculating the displacement amount of the second element of the object to be measured; have A displacement measuring device characterized by:

2. The arithmetic processing of the first numeric sequence by the first numeric sequence processing system and the arithmetic processing of the second numeric sequence by the second numeric sequence processing system are performed in parallel.

2. The displacement measuring device according to claim 1, wherein the displacement measuring device is a displacement measuring device.

3. The luminance change coordinate detection means an event-based vision camera that detects the brightness change coordinates based on the reflected light and outputs data related to the brightness change coordinates; 3. The displacement measuring device according to claim 1, wherein the displacement measuring device is a displacement measuring device.

4. The luminance change coordinate detection means a frame camera that captures a frame image of the object to be measured using the reflected light; a luminance difference calculation means for calculating a luminance difference between successive frames for calculating a luminance difference between each pixel in the plurality of frame images output from the frame camera; a luminance change coordinate extraction means for extracting, as the luminance change coordinate, a pixel for which the luminance difference between successive frames is calculated to be equal to or greater than a certain value by the luminance difference calculation means; 3. The displacement measuring device according to claim 1, further comprising:

5. Each of the first and second numeric sequence processing systems comprises: The apparatus has a displacement amount deriving means for calculating a difference value between coordinate values ​​for a combination of a plurality of brightness change coordinates included in one data group and a plurality of brightness change coordinates included in the other data group out of two data groups at different times, and deriving the most frequent value of the calculated plurality of difference values ​​as the displacement amount of the object to be measured.

5. The displacement measuring device according to claim 1, wherein the displacement measuring device is a displacement measuring device.

6. Each of the first and second numeric sequence processing systems comprises: a numerical value sequence correction means for sorting, based on coordinate values, a plurality of brightness change coordinates included in one of two data groups at different times and a plurality of brightness change coordinates included in the other data group; a displacement amount deriving means for calculating a difference value of coordinate values ​​for all combinations of a plurality of brightness change coordinates included in the one data group and a plurality of brightness change coordinates included in the other data group, in which the order after sorting is the same, and deriving the most frequent value of the calculated plurality of difference values ​​as the displacement amount of the object to be measured; 5. The displacement measuring device according to claim 1, further comprising:

7. The displacement amount deriving means A difference value of coordinate values ​​is calculated for all combinations of the plurality of brightness change coordinates included in the one data group and the plurality of brightness change coordinates included in the other data group, in which the order after sorting is the same, and for all combinations in which the difference in order after sorting is equal to or less than a predetermined value, and the most frequent value of the calculated difference values ​​is derived as the displacement amount of the object to be measured.

7. The displacement measuring device according to claim 6, wherein the displacement measuring device is a displacement measuring device.

8. The luminance change coordinate detection means cyclically sorting and outputting the coordinate values ​​of the data in a predetermined axis direction; Either the first numeric sequence processing system or the second numeric sequence processing system Instead of performing the sorting by the numeric sequence correction means, the first data group including the plurality of coordinate values ​​after the cyclic sorting by the brightness change coordinate detection means and the second data group including the plurality of coordinate values ​​after the cyclic sorting by the brightness change coordinate detection means are acquired.

8. The displacement measuring device according to claim 6 or 7.

9. Each of the first and second numeric sequence processing systems comprises: a frequency distribution array generating means for generating two frequency distribution arrays from two data groups at different times; Displacement amount deriving means; Equipped with The displacement amount deriving means obtaining a first array by performing a discrete Fourier transform on the two frequency distribution arrays; generating a second array by performing an inverse Fourier transform on the product of the obtained first arrays; The most frequent value in the generated second array is derived as the displacement amount of the object to be measured.

5. The displacement measuring device according to claim 1, wherein the displacement measuring device is a displacement measuring device.

10. an irradiation means for irradiating the object to be measured with coherent light; a luminance change coordinate detecting means for detecting a luminance change coordinate where a luminance change occurs based on the light reflected by the object to be measured, and outputting data relating to the luminance change coordinate; a displacement amount estimation means for estimating a displacement amount of the object to be measured based on data relating to the luminance change coordinates output from the luminance change coordinate detection means; Equipped with The displacement amount estimation means a first numerical sequence processing system that calculates the displacement of the first element of the object to be measured by performing arithmetic processing on a first numerical sequence consisting of a set of first elements that represent positions of the luminance change coordinates extracted from the data; a second numerical sequence processing system that performs arithmetic processing of a second numerical sequence consisting of a set of second elements that represent positions of the luminance change coordinates extracted from the data, thereby calculating the displacement amount of the second element of the object to be measured; have A displacement measurement system characterized by:

11. A device for measuring displacement according to any one of claims 1 to 9 is provided. A non-contact input device characterized by:

12. A device for measuring displacement according to any one of claims 1 to 9 is provided. A biological micromotion measuring device characterized by:

Images