JP2013181773A - Three-dimensional shape measurement instrument and object identification device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the accuracy of three-dimensional shape measurement or identification of an object.SOLUTION: A pattern light irradiation part 101 irradiates a measurement target object with predetermined pattern light. An image input part 102 changes a focal distance, and images a plurality of pieces of image data on the measurement target object irradiated with the predetermined pattern light. An association processing part 103 calculates the displacement magnitude of a corresponding local area between the plurality of pieces of image data. A three-dimensional shape measurement instrument 1 measures a three-dimensional shape of the measurement target object on the basis of the displacement magnitude.

Description

  The present invention relates to a technique for measuring or identifying a three-dimensional shape of an object.

  Conventionally, a method of measuring a three-dimensional shape of a predetermined object from a monocular camera is known. For example, in Non-Patent Document 1, zoom-in image data and zoom-out image data are acquired by changing the focal length of an optical element of a monocular camera, and a predetermined amount is determined from the displacement amount of the corresponding local region in these image data. An algorithm for measuring a three-dimensional shape of an object is disclosed.

Jun Ma and S. I. Olsen, "Depth from zooming," J. Opt. Soc. Am. A 7, 1883-1890 (1990)

  However, in the case of the three-dimensional shape measurement using the displacement amount of the local region in the image data, the local region of the image data of the measurement target object and the local region of the background image data are under a complicated background. In some cases, the measurement accuracy is lowered.

  Accordingly, an object of the present invention is to improve the accuracy of measuring or identifying the three-dimensional shape of an object.

  The three-dimensional shape measurement apparatus according to the present invention includes an irradiation unit that irradiates a measurement target object with predetermined pattern light, and a plurality of the measurement target objects irradiated with the predetermined pattern light by changing a focal length. Based on the displacement amount calculated by the imaging means for capturing image data, the displacement amount calculation means for calculating the displacement amount of the corresponding local region between the plurality of image data, and the displacement amount calculation means, the measurement And measuring means for measuring the three-dimensional shape of the target object.

  According to the present invention, the accuracy of measuring or identifying the three-dimensional shape of an object can be improved.

It is a figure which shows the system configuration | structure of the three-dimensional shape measuring apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the function structure of the three-dimensional shape measuring apparatus 1 which concerns on the 1st Embodiment of this invention. It is a figure which shows the grid of pattern light. It is a figure which shows the structure of an image input part. It is a figure which shows the structure of a matching process part. It is a figure for demonstrating the decoding result of the image data of the measurement target object obtained by irradiating pattern light. It is a figure for demonstrating the approach which makes the density of the grid of pattern light fine. It is a figure for demonstrating the approach which makes the density of the grid of pattern light fine. It is a flowchart which shows the process of the three-dimensional shape measuring apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the system configuration | structure of the object identification apparatus which concerns on the 2nd Embodiment of this invention. It is a figure which shows the function structure of the object identification apparatus which concerns on the 2nd Embodiment of this invention. It is a figure which shows the structure of a displacement vector calculation part. It is a figure for demonstrating the method to calculate the displacement vector of an identification target object. It is a flowchart which shows the process of the object identification device which concerns on the 2nd Embodiment of this invention.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments to which the invention is applied will be described in detail with reference to the accompanying drawings.

  First, a first embodiment of the present invention will be described. FIG. 1 is a diagram showing a system configuration of a three-dimensional shape measuring apparatus according to the first embodiment of the present invention. A three-dimensional shape measurement apparatus 1 according to the first embodiment measures a three-dimensional shape of a measurement target object. As shown in FIG. 1, a projector 11, a monocular camera 12, and a general-purpose computer 13 are connected to a LAN cable or the like. It is configured by connecting with.

  FIG. 2 is a diagram illustrating a functional configuration of the three-dimensional shape measuring apparatus 1 according to the present embodiment. As illustrated in FIG. 2, the three-dimensional shape measurement apparatus 1 according to the present embodiment includes a pattern light irradiation unit 101, an image input unit 102, an association processing unit 103, and a distance calculation unit 104. The pattern light irradiation unit 101 has a functional configuration realized by the projector 11. The image input unit 102 is a functional configuration realized by the monocular camera 12. The association processing unit 103 and the distance calculation unit 104 are functional configurations realized by the general-purpose computer 13.

  Next, each functional configuration shown in FIG. 2 will be described in detail. The pattern light irradiation unit 101 is a pattern light of a grid as shown in FIG. 3, that is, pattern light in which a thick line segment or a thin line segment is embedded in each area divided by horizontal lines of each vertical line, The pattern light whose grid pattern in the region (local region) is unique as a whole is irradiated. Here, assuming that the thick line segment is 2 and the thin line segment is 1, if the leftmost vertical line shown in FIG. 3 is decoded for each area divided by the horizontal line, a value is given as (21221112222...) It is done. These decoded values are uniquely given for each vertical line, and can be distinguished from values decoded for other vertical lines.

FIG. 4 is a diagram illustrating a configuration of the image input unit 102. As illustrated in FIG. 4, the image input unit 102 includes an imaging control unit 1021 and an image storage unit 1022. In a state in which the pattern light irradiation unit 101 irradiates the measurement target object with pattern light, the imaging control unit 1021 sets the focal lengths of the optical elements in the monocular camera 12 to f ₁ and f ₂ (f ₁ ≠ f ₂ ). The zoom-in image data and the zoom-out image data are picked up. Then, the imaging control unit 1021 stores a plurality of captured image data (zoomed-in image data and zoomed-out image data) in the image storage unit 1022. Here, the focal lengths f ₁ and f ₂ are given as arbitrary values that satisfy the condition of f ₁ ≠ f ₂ .

  FIG. 5 is a diagram illustrating a configuration of the association processing unit 103. As illustrated in FIG. 5, the association processing unit 103 includes a decryption unit 1031 and a displacement amount calculation unit 1032. The decoding unit 1031 decodes the zoom-in image data pattern and the zoom-out image data pattern stored in the image storage unit 1022 of the image input unit 102. Specifically, for the image data as shown in FIG. 6A, an area in which a thick line segment is detected for each area separated by horizontal lines of each vertical line of pattern light irradiated on the measurement target object. 6, where 1 is a region where a thin line segment is detected, and 0 is a region where the distance to the irradiation surface is far and where neither a thick line segment nor a thin line segment is detected, as shown in FIG. A two-dimensional decoding result is output. Note that the decoding result as shown in FIG. 6B may use any value other than 2, 1, and 0 as long as each value is unique.

Based on the decoding result obtained by the decoding unit 1031, the displacement amount calculation unit 1032 calculates the displacement amount D of the corresponding line segment between the zoom-in image data and the zoom-out image data. Specifically, as shown in the following Expression 1, the decoding result of each line segment (1 ≦ m ≦ M, 1 ≦ n ≦ N) of M rows and N columns corresponding to FIG. 3 by the zoomed-in image data was obtained. This is given using the coordinates (x _i , y _i ) of the line segment and the coordinates (x ₀ , y ₀ ) of the line segment from which the decoding result of the corresponding m-th row and n-th column based on the zoomed-out image data is obtained. That is, the displacement amount calculation unit 1032 has a one-to-one correspondence between the coordinates of the line fragments in the zoom-in image data and the coordinates of the line fragments in the zoom-out image data, and obtains the distance between the coordinates, thereby obtaining the line segment coordinates. A displacement amount D is calculated. Here, the displacement amount D is calculated for all decoding results other than 0 obtained by the decoding unit 1031. Further, the displacement amount D is larger as the distance between the monocular camera 12 and the measurement target object shown in FIG. 1 is closer, and is smaller as the distance between the monocular camera 12 and the measurement target object is longer. Represents the relative distance between

  The distance calculation unit 104 calculates an absolute distance L from the three-dimensional shape measurement apparatus 1 to the measurement target object based on the displacement amount D calculated by the displacement amount calculation unit 1032. Specifically, the distance calculation unit 104 calculates the parameter k by the following equation 2 when the displacement amount D is calculated by the above-described method under a situation where the absolute distance L ′ is known in advance. Then, the absolute distance L is calculated as shown in the following Expression 3 using the parameter k.

  Here, the spatial calculation frequency of the absolute distance L is proportional to the density of the pattern light grid in the pattern light irradiation unit 101. That is, the higher the density of the pattern light grid, the higher the spatial calculation frequency of the absolute distance L, and the lower the pattern light grid density, the lower the spatial calculation frequency of the absolute distance L. On the other hand, the higher the spatial calculation frequency of the absolute distance L, the longer the calculation time, and the lower the spatial calculation frequency of the absolute distance L, the shorter the calculation time. Therefore, the density of the grid of pattern light irradiated by the pattern light irradiation unit 101 is appropriately set in view of the required specifications (accuracy, processing time, etc.) of the assumed application. The pattern light grid may be different from that shown in FIG. 3. For example, the intersection on the grid may be two kinds of circles, large and small.

In addition, the density of the pattern light grid in the pattern light irradiation unit 101 is not constant, and an approach (Coase To Fine) in which the density of the grid of the pattern light is initially coarse and gradually finer may be applied. Good. Specifically, for the measurement target object as shown in FIG. 7A, the pattern light irradiation unit 101 first increases the density of the grid of pattern light (S _{1 in} FIG. 7B). The distance calculation unit 104 calculates a rough absolute distance L _{0, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object using the above-described method.

Next, the pattern light irradiation unit 101 is defined as follows among the absolute distances L _{0, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) obtained by the grid (m, n). Only for the rectangular area including the grid group having an absolute distance shorter than the maximum effective distance L _max (S ₂ , S _{3 in} FIG. 7C), the density of the pattern light grid is reduced. The distance calculation unit 104 calculates a more accurate absolute distance L _{1, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object using the above-described method.

Next, the pattern light irradiation unit 101 is defined as follows among the absolute distances L _{1, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) obtained on the grid (m, n). Only for a rectangular region (S ₄ , S ₅ , S _{6 in} FIG. 7D) that includes a grid group having an absolute distance shorter than the maximum effective distance L _max , the pattern light grid density is now increased. Make it fine. The distance calculation unit 104 calculates a more accurate absolute distance L _{2, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object by using the above-described method.

Here, the maximum effective distance L _max is determined by an assumed application. For example, under the assumption that the measurement target object is picked up by the robot arm after the three-dimensional shape measurement, the maximum operating range of the robot arm is given as the maximum effective distance L _max . The maximum effective distance L _max may be determined by a statistical distribution of the absolute distance L _{m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N). For example, the maximum effective distance L _max may be given as in the following Expression 4, where the average of the absolute distances L _{m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) is Avg and the standard deviation is σ.

Alternatively, the standard deviation σ may be multiplied by k to give the maximum effective distance L _max as shown in Equation 5. Here, k is given as a small non-negative integer.

  In addition, the density of the pattern light grid in the pattern light irradiation unit 101 is not uniquely determined in advance, but the density of the pattern light grid is coarsely measured for the central region of the measurement target object or a partial region with a small curvature. An approach for reducing the density of the pattern light grid may be applied to the side region of the target object and the partial region having a large curvature.

Specifically, the pattern light irradiation unit 101 first increases the density of the pattern light grid for a measurement target object as shown in FIG. 8A, for example (S _{1 in} FIG. 8B). The distance calculation unit 104 calculates a rough absolute distance L _{0, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object using the above-described method.

Next, the pattern light irradiator 101 has a side surface region (of the measurement target object) out of the absolute distances L _{0, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) obtained by the grid (m, n). Only for S ₂ and S ₃ ) in FIG. 8C, the density of the pattern light grid is made fine. The distance calculation unit 104 calculates a more accurate absolute distance L _{1, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object by using the above-described method.

Next, the pattern light irradiation unit 101 calculates the curvature of the object to be measured among the absolute distances L _{1, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) obtained on the grid (m, n). Only for a large partial region (S ₄ , S ₅ , S ₆ , S _{7 in} FIG. 8C), the density of the pattern light grid is made finer. Then, the distance calculation unit 104 calculates a more accurate absolute distance L _{2, m, n} (1 ≦ m ≦ M, 1 ≦ n ≦ N) to the measurement target object using the method described above.

  The three-dimensional shape measurement result obtained in this way is the upper layer of the three-dimensional shape measurement apparatus 1, for example, under the assumption that the measurement target object is picked up by the robot arm after the three-dimensional shape measurement, The information is transmitted to a device or a program for controlling the three-dimensional shape measuring apparatus 1 and applied to various applications.

  FIG. 9 is a flowchart showing processing of the three-dimensional shape measuring apparatus 1 according to the present embodiment. Hereinafter, the processing of the three-dimensional shape measurement apparatus 1 according to the present embodiment will be described with reference to FIG.

  In step S901, the pattern light irradiation unit 101 irradiates the measurement target object with pattern light of a grid as shown in FIG. In step S <b> 902, the image input unit 102 acquires zoom-in image data of a measurement target object imaged by pattern light irradiation by the pattern light irradiation unit 101. In step S <b> 903, the image input unit 102 acquires zoom-out image data of the measurement target object imaged by pattern light irradiation by the pattern light irradiation unit 101. In step S904, the corresponding position calculation unit 103 calculates the displacement amount D of the corresponding line segment between the zoom-in image data and the zoom-out image data. In step S905, the distance calculation unit 104 calculates the absolute distance L based on the displacement amount D.

In step S906, the distance calculation unit 104 compares the maximum effective distance _Lmax and the absolute distance L, and determines whether or not there is a rectangular region including a grid group having an absolute distance L shorter than the maximum effective distance _Lmax. judge. If there is a rectangular region including a grid group having an absolute distance L shorter than the maximum effective distance L _max , the process returns to step S901. On the other hand, when there is no rectangular area including the grid group having the absolute distance L shorter than the maximum effective distance L _max , the process ends. In step S901, the pattern light irradiation unit 101 irradiates the rectangular area with pattern light with a finer grid density. Here, the density of the pattern light grid is made fine for a rectangular region including a grid group having an absolute distance L shorter than the maximum effective distance _Lmax . On the other hand, the density of the grid of pattern light may be made fine for a predetermined region (for example, a side region, a partial region having a large curvature) of the measurement target object.

  The three-dimensional shape measuring apparatus 1 is based on the displacement amount D of the corresponding line segment between the zoom-in image data and the zoom-out image data captured with the pattern light whose grid density is controlled as described above. 3D shape measurement of the measurement object is performed.

  In the above-described embodiment, the density of the pattern light grid is controlled based on the absolute distance L. However, the pattern light irradiation range may be controlled based on the absolute distance L. For example, in the above-described embodiment, the density of the pattern light grid for a certain rectangular area is made fine based on the absolute distance L, but the irradiation range is controlled so that the pattern light is irradiated only to the rectangular area. You may do it. Further, the density of the pattern light grid and the like may be controlled based on the distribution of the absolute distance L instead of using the value of the absolute distance L as a reference.

  In the first embodiment, the measurement target object is irradiated with the pattern light whose grid pattern is unique as a whole and the three-dimensional shape thereof is measured. Therefore, the measurement accuracy of the three-dimensional shape of the measurement target object is improved. Can be improved.

  Next, a second embodiment of the present invention will be described. FIG. 10 is a diagram showing a system configuration of the object identification device according to the second exemplary embodiment of the present invention. As shown in FIG. 10, the object identification device 2 according to the second embodiment is for identifying an object to be identified, and by connecting a projector 21, a monocular camera 22, and a general-purpose computer 23 with a LAN cable or the like. Composed.

  FIG. 11 is a diagram illustrating a functional configuration of the object identification device 2 according to the present embodiment. As shown in FIG. 11, the object identification device 2 according to the present embodiment includes a pattern light irradiation unit 201, an image input unit 202, a displacement vector calculation unit 203, and an identification unit 204. Note that the pattern light irradiation unit 201 has a functional configuration realized by the projector 21. The image input unit 202 is a functional configuration realized by the monocular camera 22. The displacement vector calculation unit 203 and the identification unit 204 are functional configurations realized by the general-purpose computer 23.

  Next, each configuration shown in FIG. 11 will be described in detail. The pattern light irradiation unit 201 and the image input unit 202 have functions equivalent to those of the pattern light irradiation unit 101 and the image input unit 102 shown in FIG.

FIG. 12 is a diagram illustrating a configuration of the displacement vector calculation unit 203. As shown in FIG. 12, the displacement vector calculation unit 203 includes a decoding unit 2031, a displacement amount calculation unit 2032, a displacement vector calculation unit 2033, and a displacement vector storage unit 2034. The decoding unit 2031 and the displacement amount calculation unit 2032 illustrated in FIG. 12 have the same functions as the decoding unit 1031 and the displacement amount calculation unit 1032 illustrated in FIG. 5, and thus description thereof is omitted here. The displacement vector calculation unit 2033 calculates the displacement vector r of the corresponding line segment between the zoom-in image data and the zoom-out image data. Specifically, as shown in the following Expression 6, a decoding result of each line segment (1 ≦ m ≦ M, 1 ≦ n ≦ N) of M rows and N columns corresponding to FIG. Using the coordinates r _i (x _i , y _i ) of the line segment and the coordinates r ₀ (x ₀ , y ₀ ) of the line segment from which the decoding result of the corresponding m-th row and n-th column based on the zoomed-out image data is obtained. Given. That is, the displacement vector calculation unit 2033 associates the coordinates of the line fragments in the zoom-in image data with the coordinates of the line fragments in the zoom-out image data on a one-to-one basis, and sets the vector between the coordinates as the displacement vector r of the line fragments. calculate. For example, when the displacement vector r is calculated for the identification target object as shown in FIG. 13A, a displacement vector r unique to the identification target object as shown in FIG. 13C is obtained. FIG. 13B shows a state in which the identification target object shown in FIG. 13A is viewed from directly above. Here, the displacement vector r is calculated for all decoding results other than 0 obtained by the decoding unit 2031 and stored in the displacement vector storage unit 2034.

The identification unit 204 uses the pattern light irradiation unit 201, the image input unit 202, and the displacement vector calculation unit 203 to detect all the displacement vectors r _k (k = 0, 1, 2,... M · N) is calculated and stored in the displacement vector storage unit 2034. Similarly, the identification unit 204 uses the pattern light irradiation unit 201, the image input unit 202, and the displacement vector calculation unit 203 to detect all the displacement vectors r ′ _k (k = 0, 1, 2,... M · N) is calculated and stored in the displacement vector storage unit 2034.

Further, the discriminating unit 204 uses the normalized correlation shown in the following Expression 7 to calculate all the displacement vectors r _k (k = 0, 1, 2,... M · N) and the types of objects of known types. There calculates all unknown identification object of the displacement vector _{r'k (k = 0,1,2, ···} M · N) correlation value S (r _{k, r'k)} with the. Here, when the correlation value S (r _k , r ′ _k ) is equal to or greater than a predetermined threshold T, these two objects are determined to be of the same type. On the other hand, when the correlation value S (r _k , r ′ _k ) is equal to or less than the predetermined threshold T, these two objects are determined as different types. The predetermined threshold T is a value determined experimentally before the object identification device 2 operates in the real environment. The type may be given a correlation value S displacement vector r _k and the type of the known object is the Euclidean distance between the displacement vector _r'k unknown identification object.

  The object identification result obtained in this way is obtained by assuming that the robot arm, the object identification device 2, and the upper layer of the object identification device 2, for example, under the assumption that the object to be identified is picked up by the robot arm after object identification, It is transmitted to a device, a program, etc. for controlling and is applied to various applications.

  FIG. 14 is a flowchart showing processing of the object identification device 2 according to the present embodiment. Hereinafter, the processing of the object identification device 2 according to the present embodiment will be described with reference to FIG. Note that steps S1401 to S1404 in FIG. 14 are the same processes as steps S901 to S904 in FIG.

In step S1405, the displacement vector calculation unit 203 calculates the displacement vector r of the corresponding line segment between the zoom-in image data and the zoom-out image data. In step S1406, the identification unit 204, types and all the displacement vectors r _k of known objects, types calculates the correlation value S of all the displacement vectors _r'k unknown identification object.

  In step S1407, the identification unit 204 determines whether or not the correlation value S is greater than or equal to a predetermined threshold T. If the correlation value S is greater than or equal to the predetermined threshold T, the process proceeds to step S1408. On the other hand, if the correlation value S is less than the predetermined threshold T, the process proceeds to step S1409. In step S1408, the identification unit 204 determines that the object with the known type and the identification target object with the unknown type are the same type of object. In step S1409, the identification unit 204 determines that the known object of the type and the identification target object of the unknown type are different types of objects.

  In the second embodiment, the identification target object is irradiated with the pattern light whose grid pattern is unique as a whole to identify the identification target object, so that the identification accuracy of the object can be improved.

  The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

  1: three-dimensional shape measurement device, 2: object identification device, 11, 21: projector, 12, 22: monocular camera, 13, 23: general-purpose computer, 101, 201: pattern light irradiation unit, 102, 202: image input unit , 103: association processing unit, 104: distance calculation unit, 203: displacement vector calculation unit, 204: identification unit, 1021: imaging control unit, 1022: image storage unit, 1031: decoding unit, 1032: displacement amount calculation unit, 2031: Decoding unit, 2032: Displacement amount calculation unit, 2033: Displacement vector calculation unit, 2034: Displacement vector storage unit

Claims (16)

Irradiating means for irradiating the measurement target object with a predetermined pattern light;
An imaging means for imaging a plurality of image data of the measurement target object irradiated with the predetermined pattern light by changing a focal length;
A displacement amount calculating means for calculating a displacement amount of a corresponding local region between the plurality of image data;
A three-dimensional shape measurement apparatus comprising: a measurement unit that measures a three-dimensional shape of the measurement target object based on the displacement amount calculated by the displacement amount calculation unit.   The three-dimensional shape measuring apparatus according to claim 1, wherein the irradiation unit irradiates the predetermined pattern light whose pattern in the local region is unique as a whole.   The displacement amount calculation means associates local regions between the plurality of image data on a one-to-one basis, and calculates a distance between the associated local regions as the displacement amount. The three-dimensional shape measuring apparatus described. Based on the displacement amount calculated by the displacement amount calculating means, further comprising an absolute distance calculating means for calculating an absolute distance from the three-dimensional shape measuring apparatus to the measurement target object;
The said irradiation means controls the density of the grid of the said predetermined pattern light based on the said absolute distance calculated by the said absolute distance calculation means, The any one of Claim 1 thru | or 3 characterized by the above-mentioned. The three-dimensional shape measuring apparatus according to claim 1. Based on the displacement amount calculated by the displacement amount calculating means, further comprising an absolute distance calculating means for calculating an absolute distance from the three-dimensional shape measuring apparatus to the measurement target object;
4. The irradiation unit according to claim 1, wherein the irradiation unit controls an irradiation range of the predetermined pattern light based on the absolute distance calculated by the absolute distance calculation unit. 3D shape measuring device.   6. The three-dimensional shape according to claim 5, wherein the irradiation unit, the imaging unit, and the displacement amount calculation unit repeatedly perform processing based on the absolute distance calculated by the absolute distance calculation unit. Measuring device. Irradiating means for irradiating the identification target object with a predetermined pattern light;
Imaging means for imaging a plurality of image data of the identification target object irradiated with the predetermined pattern light by changing a focal length;
Displacement vector calculating means for calculating a displacement vector of a corresponding local region between the plurality of image data;
An object identification apparatus comprising: an identification unit that identifies the identification target object based on the displacement vector calculated by the displacement vector calculation unit.   The object identifying apparatus according to claim 7, wherein the irradiation unit irradiates the predetermined pattern light whose pattern in the local region is unique as a whole.   The identification means calculates a correlation value between the displacement vector calculated for the identification target object and a displacement vector calculated for an object of a known type, and identifies the identification target object based on the correlation value The object identification device according to claim 7 or 8, characterized in that   10. The object according to claim 9, wherein the correlation value is given by a normalized correlation between the displacement vector calculated for the identification target object and a displacement vector calculated for the object of the known type. Identification device.   10. The object identification according to claim 9, wherein the correlation value is given as a Euclidean distance between the displacement vector calculated for the identification target object and a displacement vector calculated for the object of the known type. apparatus.   12. The displacement vector calculating unit according to claim 7, further comprising: associating local regions between the plurality of image data on a one-to-one basis, and calculating a vector between the associated local regions as the displacement vector. The object identification device according to any one of the above. A three-dimensional shape measurement method executed by a three-dimensional shape measurement apparatus,
An irradiation step of irradiating a measurement target object with a predetermined pattern light; and
An imaging step of imaging a plurality of image data of the measurement target object irradiated with the predetermined pattern light by changing a focal length;
A displacement amount calculating step for calculating a displacement amount of a corresponding local region between the plurality of image data;
A three-dimensional shape measuring method comprising: a measuring step of measuring a three-dimensional shape of the measurement target object based on the displacement amount calculated in the displacement amount calculating step. An object identification method executed by an object identification device, comprising:
An irradiation step of irradiating the identification target object with a predetermined pattern light; and
An imaging step of capturing a plurality of image data of the identification target object irradiated with the predetermined pattern light by changing a focal length;
A displacement vector calculating step of calculating a displacement vector of a corresponding local region between the plurality of image data;
And an identification step of identifying the identification target object based on the displacement vector calculated by the displacement vector calculation step. Irradiation means for irradiating the measurement target object with predetermined pattern light, and imaging means for imaging a plurality of image data of the measurement target object irradiated with the predetermined pattern light by changing a focal length A program for causing a computer to execute a 3D shape measurement method executed by a 3D shape measurement apparatus,
A displacement amount calculating step for calculating a displacement amount of a corresponding local region between the plurality of image data;
A program for causing a computer to execute a measurement step of measuring a three-dimensional shape of the measurement target object based on the displacement amount calculated in the displacement amount calculation step. Irradiation means for irradiating the identification target object with a predetermined pattern light; and an imaging means for imaging a plurality of image data of the identification target object irradiated with the predetermined pattern light by changing a focal length. An object identification method executed by an object identification device, comprising:
A displacement vector calculating step of calculating a displacement vector of a corresponding local region between the plurality of image data;
A program for causing a computer to execute an identification step for identifying the identification target object based on the displacement vector calculated by the displacement vector calculation step.

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