JP6592277B2 - Measuring device, calibration method and program - Google Patents

Description

  The present invention relates to a camera calibration method for calculating camera parameters of a camera.

  A method of measuring the length and three-dimensional position (coordinates) of a subject using two cameras (stereo cameras) is known. In this method, a subject is imaged using two cameras arranged at different positions, and the length, three-dimensional position, etc. of the subject are determined based on the parallax of the subject between the two images captured by the two cameras. Is calculated. Here, camera parameters are necessary to calculate the length, three-dimensional position, etc. of the subject based on the parallax. The camera parameters include internal parameters related to the characteristics of each camera and external parameters related to the relationship between the two cameras. Examples of the internal parameters include a focal length and a distortion coefficient of a lens provided in the camera. Moreover, as an external parameter, the positional relationship between two cameras is mentioned, for example. In order to accurately measure the length and three-dimensional position of the subject, it is desirable that the camera parameters are set to values as accurate as possible.

  Therefore, Patent Document 1 discloses a camera calibration in which a calibrator having a plurality of feature points is captured by two cameras, and camera parameters are calculated based on the parallax of the calibrator between the two captured images. A method is described. Specifically, in the camera calibration method, first, a distance (in real space) between two feature points included in two images is calculated by a stereo method. Then, the camera parameter is corrected so as to minimize the error (measurement error) between the calculated distance between the two feature points and the actual distance (known).

JP 2012-202694 A (released on October 22, 2012)

  However, in the camera calibration method described in Patent Document 1, the camera parameters are corrected based only on the parallax in the baseline direction (the direction in which two cameras are arranged). That is, when correcting the camera parameter, there is a problem in that the camera parameter cannot be accurately corrected because the parallax in the direction different from the base line direction is not taken into consideration.

  The present invention has been made in view of the above problems, and an object thereof is to provide a camera calibration method for accurately calculating camera parameters.

In order to solve the above problems, a camera calibration method according to an aspect of the present invention is a camera calibration method for calculating camera parameters of a stereo camera from a stereo image obtained by imaging a subject with a stereo camera,
A distance between two points on the subject corresponding to two points on the stereo image calculated based on a first parallax that is a parallax between the stereo images in a first direction of the stereo camera; A first evaluation step for calculating a first evaluation value that is a difference from an actual distance between the two points;
A second evaluation step of calculating a second evaluation value based on a second parallax that is a parallax between the stereo images in a second direction different from the first direction;
A calibration step of calculating the camera parameter so as to minimize the first evaluation value and the second evaluation value;

  According to the present invention, camera parameters can be calculated with high accuracy.

1 is a block diagram illustrating a configuration of a stereo camera system according to Embodiment 1. FIG. It is a figure which shows an example of the calibrator in Embodiment 1. FIG. 6 is a flowchart illustrating an example of camera parameter calculation processing according to the first embodiment. It is a flowchart which shows the detail of a part of the said camera parameter calculation process. (A) is a figure which shows the image which imaged the calibrator with the pinhole camera, (b) is a figure which shows the image which imaged the calibrator with the camera provided with the lens. It is a figure which shows a mode that a square is imaged using a pinhole camera and an image is acquired. It is a figure which shows the coordinate and principal point position of each vertex of a square on the image which imaged the square. It is a figure which shows the result of having translated each vertex in FIG. 6 so that the principal point position may be located in the origin. It is a figure which shows the case where the same calibrator is each imaged with the imaging device from which a focal distance differs. It is a figure which shows the image which the imaging device imaged this calibrator in the state which inclined the optical axis with respect to the calibrator. It is a figure which shows the image which imaged this calibrator from the direction different from FIG. 9, in the state which inclined the optical axis with respect to the calibrator. FIG. 3 is a diagram illustrating an example of a relationship between a subject and an image formation position when two imaging devices constituting the stereo camera system according to the first embodiment capture an image of the subject. It is a figure which shows a mode that the optical axis and position of one imaging device which comprise the stereo camera system which concerns on Embodiment 1 have shifted | deviated. It is a figure which shows the image which an imaging device images in the stereo camera system in the state shown to FIG. It is a figure which shows the positional relationship of the one feature point of a to-be-photographed object, and the corresponding point on the image which the imaging device which concerns on Embodiment 1 images. It is a figure which shows the image which the imaging device shown to FIG. 13 (A) imaged. It is a figure which shows the state from which the position of the one imaging device which comprises a stereo camera system has shifted | deviated from the base line. 6 is a flowchart of a camera parameter calculation method according to a modification of the first embodiment. The point used as the reference | standard in the image imaged with one imaging device which comprises the stereo camera system which concerns on Embodiment 2, and the corresponding point in the image imaged with the other imaging device are shown. FIG. 17 is a diagram illustrating an x′y ′ coordinate system obtained by rotating the xy coordinate system illustrated in FIG. 16 by 45 degrees in the xy plane. FIG. 10 is a diagram illustrating a state in which the position of one imaging device constituting the stereo camera system according to Embodiment 2 is deviated from a baseline, and there is a y-direction parallax between the two imaging devices. The base line length between two imaging devices in the x′y ′ coordinate system after the xy coordinate system shown in FIG. 18A is rotated 45 degrees in the xy plane is shown.

Embodiment 1
Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

(Stereo camera system 1)
FIG. 1 is a block diagram illustrating a configuration example of a stereo camera system (camera system) 1 according to the present embodiment. As shown in FIG. 1, the stereo camera system 1 includes imaging devices (cameras) 200 a and 200 b, a control device 300, and a storage unit 400.

  The control device 300 controls the imaging devices 200a and 200b to image the calibrator (subject) 201 (see FIG. 2). The control device 300 acquires captured images of the calibrator 201 captured by the imaging devices 200a and 200b as input images, and calculates optimal camera parameters based on the input images. The storage unit 400 stores camera parameter information calculated by the control device 300.

  The control device 300 includes an image acquisition unit 301, a feature point extraction unit 302, an internal parameter calculation unit 303, an image correction unit 304, an external parameter calculation unit 305, and an imaging device control unit 306. Processing performed by each unit of the control device 300 will be described later. 1 shows a configuration in which the control device 300 and the storage unit 400 are included in the stereo camera system, the image acquisition unit 301, the feature point extraction unit 302, the internal parameter calculation unit 303, and the image related to camera parameter calculation are illustrated. The correction unit 304, the external parameter calculation unit 305, and the storage unit 400 may be configured not to be included in the stereo camera system, and an image captured by the stereo camera in advance is provided in a control device outside the stereo camera, for example, a PC. The camera parameter may be calculated by the control device.

(Calibrator 201)
FIG. 2 is a diagram illustrating an example of the calibrator 201. As illustrated in FIG. 2, the calibrator 201 has a pattern in which white squares and black squares are alternately arranged in a checkerboard pattern at regular intervals in the vertical and horizontal directions, for example. The vertices of each square have a large brightness contrast and become feature points of an image obtained by capturing the calibrator 201. In the calibrator 201, the relative positional relationship between vertices is known.

(Camera parameter calculation processing)
Next, camera parameter calculation processing in the present embodiment will be described. FIG. 3A is a flowchart illustrating an example of camera parameter calculation processing.

  In one example, in the camera parameter calculation processing, first, the imaging device control unit 306 controls the imaging devices 200a and 200b to capture the calibrator 201, and the image acquisition unit 301 performs calibration captured by each of the imaging devices 200a and 200b. Each captured image of the container 201 is acquired as an input image (S101). The feature point extraction unit 302 extracts feature points (first feature points) from the input image acquired by the image acquisition unit 301, and calculates the coordinates of the first feature points (first feature point coordinates) in the image. (S102).

  Next, the internal parameter calculation unit 303 executes an internal parameter calculation process for calculating internal parameters of the imaging devices 200a and 200b based on the first feature point coordinates calculated by the feature point extraction unit 302 (S103). The internal parameter calculation unit 303 stores the calculated internal parameter in the storage unit 400.

  Next, the feature point extraction unit 302 extracts feature points (second feature points) from the input image corrected by the image correction unit 304 using the internal parameters calculated by the internal parameter calculation unit 303, The coordinates of the second feature point (second feature point coordinates) are calculated (S104).

  Next, the external parameter calculation unit 305 calculates the external parameters of the imaging devices 200a and 200b based on the second feature point coordinates calculated by the feature point extraction unit 302 (S105). The external parameter calculation unit 305 stores the calculated external parameter in the storage unit 400. This is the end of the camera parameter calculation process.

(Internal parameter calculation process)
Next, details of the internal parameter calculation process executed as S103 of the camera parameter calculation process will be described. The internal parameter calculation unit 303 and the image correction unit 304 execute internal parameter calculation processing.

  In one example, the internal parameters calculated in the internal parameter calculation process include a focal length, a principal point position, a distortion coefficient, and the like. The internal parameter is a parameter that represents a characteristic specific to each of the imaging devices 200a and 200b, and thus can be calculated independently for each of the imaging devices 200a and 200b.

  FIG. 3B shows a flow of internal parameter calculation processing. The internal parameter calculation unit 303 first calculates a distortion coefficient and a principal point position (S103_1, details will be described later).

  Next, the image correction unit 304 corrects the distortion of the input image based on the distortion coefficient and principal point position calculated by the internal parameter calculation unit 303 (S103_2). The distortion-corrected input image approximates an image 401 without distortion (see FIG. 4A) captured by a pinhole camera. Therefore, in each processing after S103_3, it is possible to apply the pinhole camera model to the input image.

  Finally, the focal lengths of the imaging devices 200a and 200b are calculated using the corrected input image (S103_3, details will be described later). At this time, the principal point position may be recalculated (details will be described later).

  This is the end of the internal parameter calculation process.

(S103_1; calculation method of distortion coefficient k _i and principal point position (c _x , c _y ))
Here, the calculation method of the distortion coefficient and the principal point position in S103_1 (see FIG. 3B) of the internal parameter calculation process will be specifically described. First, what kind of images are specifically an image with distortion and an image without distortion will be described with a specific example.

  FIG. 4A is a diagram illustrating a distortion-free image obtained by capturing the calibrator 201 with a pinhole camera. FIG. 4B is a diagram illustrating a distorted image obtained by imaging the calibrator 201 using an imaging apparatus including a lens.

  As shown in FIGS. 4A and 4B, an image 402 captured by an imaging device including a lens is distorted with respect to an ideal image 401 captured by a pinhole camera due to lens aberration. Therefore, in S103_1, the internal parameter calculation unit 303 distorts the input image with distortion captured by the imaging devices 200a and 200b including lenses into an image without distortion as captured by an ideal pinhole camera. The parameters for correction are calculated by the following method.

The ideal first feature point coordinate calculated from the image captured by the pinhole camera is the ideal coordinate (x _pin , y _pin ), and the ideal coordinate is distorted (distortion reverse correction is performed). (X _dis , y _dis )

It is expressed as

  In equations (1) and (2), the coefficients x and y are

It is. Here, the position (c _x , c _y ) represents a principal point position that represents the intersection of the optical axis of the imaging devices 200a and 200b and the imaging device (such as CCD or CMOS) of the imaging devices 200a and 200b. R represents the distance on the image from the principal point position (c _x , c _y ) to the ideal coordinates (x _pin , y _pin ), and the coefficients x, y and the distance r are

Satisfy the relationship.

K _i is a distortion coefficient representing the distortion of the radial distortion, and is a coefficient when the distortion of the radial distortion is approximated by a 2n degree polynomial.

The expressions (1) and (2) represent the distortion coordinates (x _dis , y _dis ) considering only the radial distortion, but considering the eccentric distortion, the distortion coordinates (x _dis , y _dis ) are

Can be expressed as At this time, p _i is a distortion coefficient representing the distortion of the eccentric distortion, and is a coefficient when the distortion of the eccentric distortion is approximated by a 2n-order polynomial.

  Expressions (1), (2), (6), and (7) are expressions that take into account the distortion caused by the lens, but more appropriate distortion correction is possible by taking into account the distortion of the image sensor. .

  Next, an ideal coordinate setting method in S103_1 will be described. FIG. 5 shows how the square 501 is captured by a pinhole camera to obtain an image 401. In FIG. 5, the imaging device of the pinhole camera is arranged at a position represented by z = f (f is the focal length of the pinhole camera). Q0 (X0, Y0, Z0), Q1 (X1, Y1, Z1), Q2 (X2, Y2, Z2), and Q3 (X3, Y3, Z3) are three-dimensional coordinates of the four vertices of the square 501. Further, P0 (x0, y0, f), P1 (x1, y1, f), P2 (x2, y2, f), and P3 (x3, y3, f) are respectively the positions Q0 of the vertices of the square 501, 3D coordinates indicating the positions on the image 401 corresponding to Q1, Q2, and Q3 (projection positions on the image sensor at the vertices of the square 501), and the x and y coordinates of each of P0, P1, P2, and P3 Are coordinates on the image 401 of each of P0, P1, P2, and P3.

If the square 501 shown in FIG. 5 corresponds to one square of the calibrator 201 shown in FIG. 2, three-dimensional coordinates (X _pin , Y _pin , Z _pin ), using the three-dimensional coordinates of Q0, Q1, and Q3 and coefficients u and v that are integers,

It is expressed as

Further, the coordinates on the image 401 corresponding to the three-dimensional coordinates (X _pin , Y _pin , Z _pin ) of the vertices of the square (corresponding to the first feature points) represented by the equations (8), (9), and (10), that is, The ideal coordinates (x _pin , y _pin ) use the coordinates on the image 401 of P0, P1, and P3, the coefficients u and v, and the coefficients s and t expressed by the following equations (11) and (12). And

It is expressed as

In S103_1 of the internal parameter calculation process, the internal parameter calculation unit 303 converts the ideal coordinates (x _pin , y _pin ) expressed by the equations (13) and (14) into the equations (1), (2), (6), (7). ) Is used to calculate the difference between the distortion coordinates (x _dis , y _dis ) distorted using () and the first feature point coordinates calculated from the input images actually captured by the imaging devices 200a and 200b. The distortion coefficient and the principal point position (c _x , c _y ) are calculated so as to minimize. The parameter that minimizes the difference can be calculated using, for example, a known optimization algorithm such as Newton's method. Thereby, parameters necessary for the above-described distortion correction can be calculated.

Since the ideal coordinates (x _pin , y _pin ) are expressed by the equations (13) and (14), the calibrator 201 has a pattern in which squares as shown in FIG. 2 are alternately arranged. There is no need, and as long as the shape is known, for example, a pattern in which an arbitrary shape such as a rhombus or a rectangle is arranged may be used. In order to calculate the internal parameter, the distance between the feature points of the calibrator 201 may be unknown, but in order to calculate the external parameter, the distance between the feature points needs to be known. . Therefore, when the calibrator 201 is used when calculating the external parameter, the distance between the feature points of the calibrator 201 needs to be known.

Further, when the distortion coordinates (x _dis , y _dis ) and the principal point position (c _x , c _y ) are calculated by the above-described method, if the distortion of the image 402 is large, the distortion center, that is, the principal point position (c _x , _cy ) can be calculated with high accuracy. However, when the distortion of the image 402 is small, the calculated principal point position (c _x , c _y ) can be accurately corrected even if the calculated principal point position (c _x , c _y ) is deviated from the actual principal point position. There is a possibility that the point position (c _x , c _y ) and the actual principal point position are shifted. Therefore, it is preferable that the internal parameter calculation unit 303 recalculates the principal point position (c _x , c _y ) when calculating the focal length described later.

  In addition, it is preferable that the feature points are evenly distributed in the entire input image obtained by capturing the calibrator 201 because the weights at the respective positions of the input image are equalized during optimization. Therefore, when the imaging devices 200a and 200b image the calibrator 201, the imaging devices 200a and 200b and the like are set so that the optical axis and the calibrator 201 are substantially perpendicular and the feature points are imaged on the entire screen. It is desirable.

(S103_3; calculation method of focal length f)
Next, the calculation method of the focal length f in S103_3 (see FIG. 1B) of the internal parameter calculation process will be specifically described.

FIG. 6 shows the coordinates P60 (x60, y60), P61 (x61, y61), P62 (x62, y62), and P63 (x63, y63) of each vertex of the square on the image 601 obtained by capturing the square with a pinhole camera. And principal point positions (c _x , c _y ).

FIG. 7 shows an image 701 and coordinates P70, P71, P72, and P73 obtained by translating the images 601 and P60, P61, P62, and P63 shown in FIG. 6 with the principal point position (c _x , c _y ) as the origin. Is shown. The coordinates of P70 (x70, y70) are

It is expressed as Other coordinates P71 (x71, y71), P72 (x72, y72), and P73 (x73, y73) are also coordinate P61 (x61, y61), P62 (x62, y62), P63 (x63, y63) is expressed in coordinates obtained by translation.

  The focal length f can be calculated from the following equation (19) using the coordinates of P70, P71, and P73 and the coefficients s7 and t7 represented by the following equations (17) and (18).

  Here, when the imaging devices 200a and 200b image the calibrator 201 in a state substantially perpendicular to the calibrator 201, both s7 and t7 in the equations (17) and (18) are small values, and the equation (19) Since the denominator is also a small value, the influence of the error of s7 and t7 on the calculation result of the focal length f becomes large. That is, the calculation accuracy of the focal length f according to the equation (19) decreases.

  This will be described with reference to the drawings. FIG. 8 is a diagram illustrating a case where the same calibrator 201 is imaged by the imaging device 801 having the focal length f1 and the imaging device 802 having the focal length f2. Here, both the imaging device 801 and the imaging device 802 image the calibrator 201 in a state substantially perpendicular to the calibrator 201. The distance from the imaging device 801 to the calibrator 201 is Z1, and the distance from the imaging device 802 to the calibrator 201 is Z2. In FIG. 8, when f2 = 2 × f1 and Z2 = 2 × Z1, the calibrator 201 on the image 402 captured by the imaging device 801 and the calibrator 201 on the image 402 captured by the imaging device 802 are It becomes difficult to distinguish. Therefore, the input image used for calculating the focal length f is suitable for an image captured by tilting the optical axis with respect to the calibrator 201 because the calculation accuracy of the focal length f is high.

  FIG. 9 is a diagram illustrating an image obtained by capturing the calibrator 201 in a state in which the imaging apparatus tilts the optical axis with respect to the calibrator 201. The internal parameter calculation unit 303 selects an arbitrary square in the image 402 captured by the imaging device, and calculates the coordinates of the four vertices P70, P71, P72, and P73 that the square has. Then, the focal length f is calculated from the coordinates of P70, P71, P72, and P73 using equations (17), (18), and (19). Here, as described above, when the difference between the absolute value of s7 and the absolute value of t7 in equations (17) and (18) is small, the error in the denominator of equation (19) is also small, and based on equation (19). The calculation accuracy of the focal length f decreases. Therefore, it is desirable that the internal parameter calculation unit 303 appropriately selects the square so that the difference between the absolute value of s7 and the absolute value of t7 is large. In addition, the internal parameter calculation unit 303 can further improve the calculation accuracy of the focal length f by calculating the focal length f using a plurality of images.

(S103_3; recalculation method of principal point position (c _x , c _y ))
Here, the recalculation method of the principal point position (c _x , c _y ) in S103_3 (see FIG. 1B) of the internal parameter calculation process will be specifically described. As described above, the principal point position (c _x , c _y ) has already been calculated in S103_1, but the distortion of the image 402 (see FIG. 4B) captured by the imaging devices 200a and 200b is small. , The principal point position (c _x , c _y ) calculated in S103_1 may be deviated from the actual principal point position. As shown in the equations (15) and (16), the coordinates P70, P71, P72, and P73 of each vertex of the square are represented by coordinates centered on the principal point position (c _x , c _y ). When the coordinates indicating the position (c _x , c _y ) are deviated from the actual principal point position, the focal length f calculated based on the coordinates P70, P71, P72, and P73 may also deviate from the actual focal length. There is. Therefore, in S103_3, when calculating the focal length f, again the main point position is internal parameter calculating part 303 _(c x, c _y) by calculating a focal length f and principal point _(c x, _{c y} ) Calculation accuracy can be improved.

The focal length f calculated from the equation (19) is selected if the principal point position (c _x , c _y ) and the coordinates P70, P71, P72, P73 of each vertex of the grid of the calibrator 201 are correct. The same value regardless of the square. Therefore, the internal parameter calculation unit 303 selects a plurality of different squares, calculates the focal length fi (i = 1, 2,...) Based on the coordinates indicating the position of each vertex of each square, The principal point position (c _x , c _y ) is calculated so that the focal distance fi becomes the same value regardless of the square, and the focal distance f is calculated based on the calculated principal point position (c _x , c _y ). . The optimization of the principal point position (c _x , c _y ) can be performed using a known optimization algorithm such as Newton's method. For example, an average value f _ave of the focal length fi calculated from the vertex coordinates of each square and an evaluation value E _{f of} the principal point position (c _x , c _y ) are respectively obtained.

Then, the internal parameter calculation unit 303 may calculate the principal point position (cx, cy) at which the evaluation value E _f is minimum. Further, the internal parameter calculation unit 303 may set the average value f _ave when the evaluation value E _f is minimum as the focal length f.

According to the above method, the calculation accuracy of the principal point position (c _x , c _y ) by the internal parameter calculation unit 303 is improved, and the calculation accuracy of the focal length f is also improved. The reason is as follows.

First, in an ideal pinhole camera, if the principal point position (c _x , c _y ) is correct, the calculated focal length f becomes the same value regardless of the selected square. In practice, however, the coordinates of the vertices extracted by the feature point extraction unit 302 may contain an error, so the internal parameter calculation unit 303 may not always be able to calculate the correct value of the focal length f. Absent. When the focal length f is calculated from the coordinates of each vertex (first feature point) of one square, the calculation error of the coordinates of the first feature point is reflected in the calculation error of the focal length f.

On the other hand, according to the above configuration, the coordinates of the first feature point are calculated for each of the plurality of squares, the focal distance fi is calculated for each calculation result of the coordinates, and the plurality of focal distances fi (i = 1, 2). ,...) _Is calculated as the focal length f. Thereby, the influence which the error contained in the calculation result of the coordinate of a 1st feature point has on the calculation result of the focal distance f can be reduced. That is, the calculation accuracy of the focal length f is improved.

In addition, the internal parameter calculation unit 303 may limit the position for selecting a square from the image 402 based on the above-described calculation result of the distortion coefficient. Thereby, the calculation accuracy of the focal length f can be further improved. As described above, since the distortion coefficient is calculated by evaluating the difference between the distortion coordinates (x _dis , y _dis ) and the actual first feature point coordinates, the internal parameter calculation unit 303 calculates the difference. As an index, it is possible to know the accuracy of distortion correction for each first feature point coordinate. Then, the internal parameter calculation unit 303 excludes the position of the first feature point around the first feature point where the accuracy of distortion correction is insufficient from the selection range of the square, so that the first distortion correction accuracy is high. The focal position can be calculated from a square including only feature points. In particular, since Equation (19) is an equation assuming a pinhole camera model, only the first feature point with high distortion correction accuracy, that is, only the first feature point to which the pinhole camera model can be applied, It is preferable to calculate the focal length.

Further, when the internal parameter calculation unit 303 calculates the average value f _ave of the plurality of focal lengths fi (i = 1, 2,...) As the focal length f, the plurality of focal lengths fi (i = 1, 2). ,...) _{May be} excluded, and the average value f _ave may be calculated. Thereby, the calculation accuracy of the focal length f can be further improved. There is a high possibility that the focal length calculated from the square including the vertex coordinates having a large error has a large deviation from the actual focal length. For this reason, the internal parameter calculation unit 303 calculates a mean value f _ave using a plurality of focal lengths fi (i = 1, 2,...) Excluding the maximum value and the minimum value, thereby generating a large error. There is a high possibility that the focal length can be calculated by excluding the square including the vertex coordinates, and the calculation accuracy of the focal length f can be improved.

  In addition, the internal parameter calculation unit 303 can further improve the calculation accuracy of the focal length f by calculating the focal length f using a plurality of images obtained by capturing the calibrator 201. FIG. 10 shows an image obtained by capturing the calibrator 201 from a direction different from that in FIG. 9 with the optical axis inclined with respect to the calibrator 201 as in FIG. The internal parameter calculation unit 303 calculates the focal length fi (i = 1, 2,...) As described above using each of the image 402 in FIG. 9 and the image 402 in FIG. By averaging the focal length fi (i = 1, 2,...), It is possible to calculate the focal length f with high accuracy. In this way, by using a plurality of images obtained by imaging the calibrator from different directions, errors included in the focal lengths calculated from the vertex coordinates of each square can be averaged to improve accuracy.

  In the present embodiment, the method of calculating the focal length f using the calibrator 201 whose pattern is configured with a square has been described. However, the calibrator 201 whose pattern is configured with a shape other than a square is used. May be.

  For example, when the focal length f is calculated from a rectangle having an aspect ratio of N: 1 (N is a natural number), the length of the side corresponding to the line segment P70-P71 shown in FIG. 7 and the side corresponding to the line segment P71-P72 If the ratio to the length of N is N: 1, the internal parameter calculation unit 303 sets the focal length f to

Can be calculated as

As described above, the internal parameter calculation unit 303 calculates the first feature point coordinates from the input image obtained by capturing the calibrator 201, and based on the calculated first feature point coordinates, the distortion coefficient k _i and the principal point position ( c _x , c _y ) are calculated (S103_1). Then, the image correction unit 304 uses the distortion coefficient k _i and the principal point position (c _x , c _y ) calculated by the internal parameter calculation unit 303 to distort the input image to obtain a focal length calculation image ( S103_2). The internal parameter calculation unit 303 selects a plurality of squares from the focal length calculation image corrected by the image correction unit 304, calculates the focal length f based on the vertex coordinates of the selected squares, and determines the principal point position. (Cx, cy) is recalculated (S103_3).

(S105: external parameter calculation method)
Here, the external parameter calculation method in S105 (see FIG. 1A) of the camera parameter calculation process will be specifically described. The external parameter is a parameter representing the positional relationship between the plurality of imaging devices 200a and 200b provided in the stereo camera system 1.

  The external parameter calculation unit 305 captures two input images (stereo images) obtained by capturing a subject having a known length (for example, an arbitrary square of the calibrator 201) with a stereo camera (a combination of the imaging device 200a and the imaging device 200b). ) To measure the length of the subject (stereo measurement). Then, the external parameter calculation unit 305 calculates an external parameter representing the positional relationship between the imaging device 200a and the imaging device 200b by comparing the measurement result of the subject length with the actual length of the subject. Here, the external parameter calculation unit 305 uses the input image (focal length calculation image) corrected by the image correction unit 304 in step S103 of the camera parameter calculation process as a stereo image used for calculating the external parameter.

  FIG. 11 is a diagram illustrating an example of a positional relationship between the subject and the imaging positions of the images 402a and 402b when the subject is imaged by the imaging device 200a and the imaging device 200b that form the stereo camera system. FIG. 11 is a diagram of the imaging device 200a disposed on the left side and the imaging device 200b disposed on the right side as viewed from above (y direction). The baseline length tx (external parameter) in the x direction of the imaging apparatus 200a is not zero. Further, the baseline length ty (external parameter) in the y direction and the shift tz in the z direction are both zero. Here, in this specification, “base length in a specific direction” means a component in a specific direction of the shortest distance between the imaging device 200a and the imaging device 200b. For example, the base length tx in the x direction is the length in the x direction of the line segment connecting the imaging device 200a and the imaging device 200b, and the baseline length ty in the y direction is a line connecting the imaging device 200a and the imaging device 200b. The length in the y direction. Assume that the focal lengths of the two imaging devices 200a and 200b are both f, and the principal point position is the center of the imaging devices 200a and 200b.

  In FIG. 11, the external parameter calculation unit 305 calculates the three-dimensional coordinates (X1101, Y1101, Z1101) of a point P1103 on the subject from the stereo image (images 402a, 402b) based on the following formula. Here, the x coordinates of the feature points (second feature points) p1103a and p1103b corresponding to the point P1103 on the subject in the images 402a and 402b captured by the imaging devices 200a and 200b are dx1 and dx2, respectively. Further, the focal length of the imaging devices 200a and 200b is assumed to be f. The base line length in the x direction between the imaging devices 200a and 200b is assumed to be tx. The y coordinate of the feature points (second feature points) p1103a and p1103b corresponding to the point P1103 on the subject in the images 402a and 402b is dy1 (not shown). The parallax in the x direction between the image 402a and the image 402b is dx = dx2-dx1.

  Here, in this specification, “parallax” means a difference in position coordinates of the same feature point between stereo images 402a and 402b captured by different imaging devices 200a and 200b. “Parallax in a specific direction” means a component of a specific direction of parallax. For example, when the image 402a and the image 402b have the same scale, the parallax (first parallax) dx in the x direction is obtained by calculating the position coordinate of the feature point p1103a in the image 402a and the position coordinate of the feature point p1103b in the image 402b. Means the x component of the connected vector. The parallax in the y direction (second parallax) dy means the y component of the same vector.

In Expressions (23), (24), and (25), since the unknown is only the baseline length tx in the x direction, the external parameter calculation unit 305 determines the three-dimensional coordinates (X1101, Y1101, P1103) when the baseline length tx is determined. Z1101) can be calculated. The external parameter calculation unit 305 determines two feature points on the images 402a and 402b corresponding to the two points P1103 and Q1103 on the subject in order to determine the baseline length tx in the x direction (first direction), which is an unknown number. Second feature point) is extracted, and the three-dimensional coordinates of the points P1103 and Q1103 corresponding to the two second feature points are calculated using the equations (23), (24), and (25), and the calculated points P1103, An error (first measurement error) between the distance on the subject measured from the three-dimensional coordinates of Q1103 and the actual distance is calculated (first evaluation step). Then, the base line length tx at which the error is zero or minimum is calculated (calibration step). For example, in FIG. 11, the distance D _stereo between the point P1103 and the point Q1103 is

It is represented by On the other hand, if the actual distance between the two points P-Q and _{D real,} the difference between the distance _{D stereo} and the distance _{D real} delta _D (first measurement error), the following (27) or (28) Represented by

Here, a pinhole camera model can be applied to the stereo camera that captures the subject (that is, the internal parameter calculation unit 303 can accurately calculate the internal parameter and has been corrected by the image correction unit 304). The input image is assumed to be completely distorted), so that when the baseline length tx, which is an external parameter, is correct, the point on the subject measured based on the images 402a and 402b captured using a stereo camera The distance D _stereo between P1103 and Q1103 is equal to the actual D _real between the points P1103 and Q1103 on the subject. Thus, in the formula (27) or formula (28), the base line length tx when the difference delta _D is zero, the optimum external parameters. However, because they may contain an error in calculating the second feature point coordinates from the input image, there is a possibility that the difference delta _D does not become zero. In this case, the external parameter calculating unit 305 determines the tx to minimize the difference delta _D as external parameters (calibration step).

The external parameter calculation method has been described above using FIG. 11 as an example. Expressions (23), (24), and (25) are applicable when captured by a stereo camera having the configuration shown in FIG. On the other hand, for example, when there is a deviation of the optical axis between the imaging devices 200a and 200b, the calculation of the three-dimensional coordinates of the point on the subject corresponding to the specific feature point is performed based on the equations (23), (24), and (25). If done, incorrect three-dimensional coordinates are calculated. In this case, tx difference delta _D is minimized is not a correct value of the external parameter to be determined.

Therefore, in the above case, the external parameter calculation unit 305 converts the input image captured by the stereo camera into an image to which Expressions (23), (24), and (25) can be applied. This image conversion is called rectification (details will be described later). The external parameter calculator 305 calculates the distance _{D stereo} between two points on the subject corresponding to the two second feature point in the image 402a, 402b after the rectification, the distance _{D stereo} and a calculation result comparing the distance D _real between two points in the actual subject, so as to minimize the difference delta _D therebetween, to calculate the external parameters.

Here, since the external parameters necessary for rectification are unknown numbers, the external parameter calculation unit 305 performs measurement using the input image after rectification by a method using a known optimization algorithm such as Newton's method. optimizing the distance between two points, the external parameters to minimize the difference delta _D and the distance between the actual of the two points on the subject. However, as described above, in the case of performing the optimization based only on the distance between two specific points, errors in certain external parameters, to compensate possible to modify other external parameters, the difference delta _D is minimum In some cases, incorrect external parameters may be calculated. When the erroneous external parameter is applied to measure the distance between two other points, the difference from the actual distance between the two points becomes large. Therefore, the external parameter calculation unit 305 may calculate an external parameter that minimizes the difference between the measured distance between any two points on the subject and the actual distance in order to calculate a correct external parameter. When both the internal parameter and the external parameter are correct, the distance on the subject measured from any two points on the image is equal to the actual distance. Therefore, the external parameter calculation unit 305 calculates the difference between the distance D _stereo between the two points on the subject measured based on the image and the actual distance D _real for the plurality of sets of second feature points, It is preferable to calculate the external parameters so as to minimize the difference.

  For example, as shown in FIGS. 9 and 10, the input image used for calculating the external parameter may be an image obtained by capturing the calibrator 201 with the optical axis inclined with respect to the calibrator 201. These images can distribute points corresponding to the second feature points in various directions in the three-dimensional space, and can select combinations of a plurality of second feature points with different conditions. It is suitable as an image used for parameter calculation. Further, a combination of a plurality of second feature points having different distance (z coordinate) conditions is selected from a plurality of images obtained by capturing the calibrator 201 by changing the distances from the imaging devices 200a and 200b to the calibrator 201. Can do. Therefore, such an image is also suitable as an image used for calculating external parameters. Note that the rectification may be applied only to the second feature point coordinates calculated from the image. In the above-described configuration, the external parameter calculation unit 305 does not need to rectify the entire image in order to calculate the external parameter based on the coordinates of the second feature point included in the image. The amount of processing can be reduced by applying only to it.

(Rectification)
Here, the rectification method will be specifically described.

FIG. 12A is a diagram illustrating a state in which the optical axis of the other imaging device 200b is inclined and the position in the z direction is shifted with respect to one imaging device 200a constituting the stereo camera system. . Here, the focal length of the imaging device 200a is f1, and the focal length of the imaging device 200b is f2. The base length in the x direction is tx, and the base length in the y direction is ty (not shown). The shift in the z direction between the imaging device 200a and the imaging device 200b is tz. As shown in FIG. 12A, the optical axis of the imaging device 200b is -θy with respect to the optical axis of the imaging device 200a, the angle about the y axis is -θx, and the angle about the x axis is -θx (see FIG. 12A). It is only tilted. FIG. 12B is a diagram illustrating images 402a and 402a captured by the imaging devices 200a and 200b in the stereo camera system in the state illustrated in FIG. FIG. 12B shows the principal point position (c _x 1, c _y 1) of the imaging device 200a and the principal point position (c _x 2, c _y 2) of the imaging device 200b. As shown in FIG. 12B, the optical axis of the imaging device 200b is tilted by −θz around the z axis with respect to the optical axis of the imaging device 200a.

  Hereinafter, in FIGS. 12A and 12B, a description will be given of a case where the external parameter calculation unit 305 rectifies an image 402b captured by the imaging device 200b with reference to an image 402a captured by the imaging device 200a.

  FIG. 13A is a diagram showing a positional relationship between a point P13 (X1301, Y1301, Z1301) on the subject and a corresponding feature point p13 on the image 402b captured by the imaging device 200b. FIG. 13B is a diagram illustrating an image 402b captured by the imaging device 200b illustrated in FIG. In FIG. 13B, feature points p13 (x1301, y1301) indicate feature points on the image 402b shown in FIG. 13A. The feature point p13 corresponds to the point P13 (X1301, Y1301, Z1301) on the subject shown in FIG.

  In the rectification, first, the external parameter calculation unit 305 corrects the difference between the focal length f1 of the imaging device 200a and the focal length f2 of the imaging device 200b. The coordinates (x1302, y1302) indicating the position of the corrected point p13 are:

It is expressed as Next, in order to align the optical axis directions of the imaging device 200a and the imaging device 200b, the external parameter calculation unit 305 sets θx around the x axis, θy around the y axis, θz around the z axis, and the position of the point p13. Rotate. The coordinates (x1303, y1303) indicating the position of the point p13 after rotation are

It is expressed as Here, in the equations (31) and (32), r1 to r9 are

It is. Next, the external parameter calculation unit 305 corrects the deviation of the principal point position between the imaging device 200a and the imaging device 200b. The coordinates (x1304, y1304) indicating the position of the corrected point p13 are

It becomes. As described above, the external parameter calculation unit 305 can calculate the coordinates (x1304, y1304) indicating the position of the rectified point p13 by the conversion from Expression (29) to Expression (35). Further, the three-dimensional coordinates of the point P13 on the corresponding subject can be calculated using the equations (23), (24), and (25). However, Expressions (23), (24), and (25) are established when the shift tz in the z direction is zero.

  Subsequently, a case where the shift tz in the z direction is not zero will be described. FIG. 14 is a diagram illustrating a state in which the position (position in the z direction) of one imaging device 200b configuring the stereo camera system 1 is deviated from the base line (x axis). That is, FIG. 14 shows a stereo camera system when the shift tz is not zero. As shown in FIG. 14, when the x coordinate of the feature point p1403a on the image 402a is dx1, the x coordinate of the feature point p1403b on the image 402b is dx2, and the parallax in the x direction is dx = dx1−dx2. The three-dimensional coordinates (X1401, Y1401, Z1401) of the point P1403 on the subject corresponding to the feature points p1403a, p1403b are

It is expressed.

Here, as in the above-described method, the external parameter calculation unit 305 performs the coordinates indicating the position of the second feature point on the image 402a captured by the reference image capturing apparatus 200a and the image captured by the image capturing apparatus 200b. The three-dimensional coordinates of the point on the subject are calculated from the coordinates obtained by rectifying the coordinates of the same second feature point. Then, the external parameter calculation unit 305 minimizes the difference between the distance D _stereo between the two points on the subject measured from the calculated three-dimensional coordinates and the actual distance D _real (known) between the two points. Calculate the parameters. At this time, the external parameter calculation unit 305 calculates the difference between each distance D _stereo measured from the plurality of sets of second feature points and the actual distance D _real, and external parameters so that these differences are minimized. By calculating the parameters, highly accurate external parameters can be calculated.

  The external parameter calculation method has been described above. As shown in equations (23), (24), (25), (36), (37), and (38), the equation for calculating the three-dimensional coordinates includes Baseline length ty is not included. However, since tx, ty, tz, θx, θy, and θz influence each other, in order to correctly calculate the external parameters, it is necessary to optimize including ty.

  Therefore, the external parameter calculation unit 305 minimizes not only the evaluation value (measurement error) based on the parallax in the x direction (first parallax) but also the evaluation value based on the parallax in the y direction (second parallax). The external parameters are calculated. Specifically, in FIG. 11, when the parallax in the y direction is dy, the three-dimensional coordinates (X1102, Y1102, Z1102) on the subject corresponding to the feature points (dx1, dy1) are

It is expressed. The external parameter calculation unit 305 calculates the three-dimensional coordinates of two points on the subject using the parallax dx, measures the distance between the two points, and calculates the difference (first evaluation value) from the actual distance. Along with calculating (first evaluation step), the three-dimensional coordinates of two points on the subject are calculated using the equations (39), (40), (41) and the parallax dy, the distance between the two points is measured, By calculating the difference (second evaluation value) from the actual distance (second evaluation step) and calculating the external parameters so as to minimize the respective evaluation values (calibration step), all the external parameters are calculated. Can be optimized.

Here, if _D the distance between two points on the object measured using the disparity dx in the x direction _{Stereo_x,} the distance between two points on the subject measured using the disparity dy in the y direction and _{D Stereo_y,} the difference delta _D between the actual distance _{D real} is expressed by the following equation (42) or (43). External parameter calculation unit 305 may calculate the extrinsic parameters to minimize the difference delta _D. The calculation of the external parameters that minimize the difference delta _D, for example, may be a known optimization algorithm such as Newton's method.

  As described above, according to the configuration of the present embodiment, the subject (for example, the calibrator 201) calculated in consideration of the parallax in the x direction (first parallax) dx and the parallax in the y direction (second parallax) dy. By evaluating the difference between the distance between the two points above and the actual distance, all external parameters can be optimized. Thereby, it is possible to calculate the external parameter with higher accuracy.

(Modification 1)
In one variation, the external parameter calculation unit 305, based on the calculation result of the distortion coefficient k _i described above, may limit the position of the second feature point selected from the image. Thereby, the calculation accuracy of the external parameters can be further improved. As described above, when calculating the distortion coefficient, the internal parameter calculation unit 303 evaluates the difference between the distortion coordinates (x _dis , y _dis ) obtained by distorting the ideal coordinates and the coordinates of the actual feature points. Therefore, the accuracy of distortion correction with respect to the coordinates of each feature point is known, and the external parameter calculation unit 305 determines a region including a feature point with insufficient accuracy of distortion correction and a feature point around the feature point. Feature points are extracted from the excluded area (specific image area) (image area extraction step). As a result, the external parameters can be optimized using only the feature points with high distortion correction accuracy, so that the external parameters can be calculated with high accuracy. Since the formula used for optimizing the external parameters described above is a formula assuming a pinhole camera model, the second feature point that increases the accuracy of distortion correction, that is, the second feature to which the pinhole camera model can be applied. Using only the feature points, the distance between two points on the subject can be measured and compared with the actual distance, which is preferable. Moreover, the accuracy of the external parameters can be further improved by excluding the combination of the second feature points having a large difference between the measured distance between the two points on the subject and the actual distance from the evaluation target.

(Modification 2)
In this embodiment, the method of calculating the internal parameter and the external parameter independently has been described. However, the method of calculating the camera parameter in consideration of the parallax dx in the x direction and the parallax dy in the y direction can also be applied to a method of calculating the internal parameter and the external parameter at the same time. An example of a camera parameter calculation method when the internal parameter and the external parameter are calculated simultaneously will be described below.

  FIG. 15 is a flowchart of a camera parameter calculation method according to this modification. In the camera parameter calculation method illustrated in FIG. 15, first, the image acquisition unit 301 captures an image (input) obtained by capturing a calibrator 201 whose relative positional relationship between feature points is known by a stereo camera (imaging devices 200a and 200b). (Image) is acquired (S1501). Next, the feature point extraction unit 302 extracts feature point coordinates from the input image captured by the calibrator 201 (S1502).

  Next, the internal parameter calculation unit 303 and the external parameter calculation unit 305 calculate x-direction parallax (first parallax) and y-direction parallax (second parallax) based on the calculated feature point coordinates. To do. Then, the internal parameter calculation unit 303 and the external parameter calculation unit 305 are configured such that the difference between the distance between the two points on the calibrator 201 measured using the parallax in the x direction and the actual distance between the two points, and By simultaneously minimizing the difference between the distance between two points on the calibrator 201 measured using the parallax in the y direction and the actual distance between the two points, the internal parameter and the external parameter are simultaneously optimized. (S1503). However, when calculating the internal parameter and the external parameter more accurately, as described above, the internal parameter and the external parameter should be calculated independently. This is because the mutual influence between the internal parameter and the external parameter can be reduced.

  As described above, in the camera calibration method for minimizing the difference between the distance measured by stereo measurement and the actual distance, by optimizing the camera parameters in consideration of both the parallax in the x direction and the parallax in the y direction, All camera parameters can be calculated accurately. In addition, by calculating the internal parameter and the external parameter independently, each parameter can be calculated accurately while preventing the error caused by the internal parameter and the error caused by the external parameter from affecting each other. Can do. Further, by calculating the camera parameters using only the feature points to which the pinhole camera model can be applied based on the distortion correction result, it is possible to improve the calculation accuracy of the camera parameters.

[Second Embodiment]
Another embodiment of the present invention will be described with reference to FIGS. For convenience of explanation, members having the same functions as those described in the embodiment are given the same reference numerals, and descriptions thereof are omitted.

  In the stereo camera system 1 (see FIG. 3) according to the first embodiment, when the baseline length ty in the y direction between the two imaging devices 200a and 200b is small, the parallax dy in the y direction becomes a value close to zero. Therefore, when the base line length ty and the parallax dy are small, if the parallax dy includes an error, the value of the z coordinate Z1102 of the feature point Q calculated by the equation (39) described in the first embodiment is greatly affected. .

  In Expression (39), when the base line length ty and the parallax dy are small, for example, when tz = 0, f = 5000, dy = 1, ty = 1, and dy = 1, Z1102 = 5000. In this case, when 1 is added to dy and dy = 2, Z1102 = 2500, and the value of Z1102 changes greatly. On the other hand, when the base line length ty and the parallax dy are large, for example, when ty = 100 and dy = 100, Z1102 = 5000. In this case, when 1 is added to dy and dy = 101, Z1102≈4950, and the value of Z1102 does not change much.

  Therefore, in the present embodiment, when the baseline length ty and the parallax dy are small, the external parameter calculation unit 305 performs coordinate transformation from the y axis to the y ′ axis in order to increase the baseline length ty and the parallax dy (coordinate transformation step). ).

  FIG. 16 shows a reference point p16 in an image 402a captured by one imaging device 200a that constitutes the stereo camera system 1, and a corresponding point q16 in an image 402b captured by another imaging device 200b. dx and dy are parallaxes in the x and y directions between the point p16 and the point q16. As shown in FIG. 16, when the baseline length ty is small, the external parameter calculation unit 305 expands the parallax after coordinate conversion by calculating the coordinates of the points p16 and q16 after coordinate conversion.

  FIG. 17 is a diagram in which the images 402a and 402b in the xy coordinate system shown in FIG. 16 are coordinate-converted into images 402a ′ and 402b ′ in the x′y ′ coordinate system rotated by 45 degrees in the xy plane. The coordinates indicating the positions of the point p16 and the point q16 shown in FIG. 16 change to a point p17 (x1701, y1701) and a point q17 (x1702, y1702), respectively, by coordinate conversion. If the rotation angle is θ,

It becomes.

  As illustrated in FIG. 17, the parallax dy ′ (second parallax) in the y ′ direction after the coordinate conversion is sufficiently larger than the parallax dy illustrated in FIG. 16. The three-dimensional coordinates (X1102 ′, Y1102 ′, Z1102 ′) on the subject corresponding to the feature points are calculated by substituting the parallax dy ′ instead of the parallax dy into the equations (39), (40), and (41). Then

It becomes. In equations (48), (49), and (50), dx ′ and dy ′ represent parallaxes in the x ′ direction and y ′ direction, respectively, and dx1 ′ and dy1 ′ are features in the x′y ′ coordinate system, respectively. The x coordinate and y coordinate of the point are represented, and ty ′ represents the baseline length in the y ′ direction.

  In FIG. 18A, the position in the y direction of one imaging device 200b constituting the stereo camera system 1 is shifted (ty ≠ 0), and the parallax in the y direction between the two imaging devices 200a and 200b. It is a figure which shows the state which exists. tx represents the baseline length in the x direction, and ty represents the baseline length in the y direction.

  18B shows a baseline length tx ′ between the two imaging devices 200a and 200b in the x′y ′ coordinate system after the xy coordinate system shown in FIG. 18A is rotated 45 degrees in the xy plane. ty 'is shown. As shown in FIGS. 17 and 18B, coordinate transformation (rotation of the xy axis) rotates the x direction in the x ′ direction and the y direction in the y ′ direction, and the base line lengths tx and ty are also parallax. Since dx ′ and dy ′ change in the same manner, the baseline lengths tx ′ and ty ′ after the coordinate conversion can be calculated from the baseline lengths tx and ty before the coordinate conversion.

  The external parameter calculation unit 305 calculates the three-dimensional coordinates on the subject corresponding to the feature points after the coordinate conversion. Thereby, since the parallax dy ′ is sufficiently larger than the parallax dy, the influence of the error included in the parallax dy ′ on the z coordinate in the calculation result of the three-dimensional coordinates on the subject is reduced, and the reliability is higher. Thus, the three-dimensional coordinates on the subject corresponding to the feature point can be calculated. Therefore, highly accurate external parameters can be calculated in both the x ′ direction and the y ′ direction.

  The rotation angle of the coordinates does not have to be 45 degrees, and may be set to an optimum angle based on the baseline lengths tx and ty. For example, the rotation angle θ is

Then, the parallax dx ′ in the x ′ direction and the parallax dy ′ in the y ′ direction after the coordinate conversion are preferable because they have the same size. Note that max (| tx |, | ty |) in equation (51) means the larger of the absolute value of the baseline length tx and the absolute value of the baseline length ty. Further, min (| tx |, | ty |) in Equation (51) means the smaller one of the baseline length tx and the baseline length ty.

  In the example illustrated in FIG. 17, the base line length ty in the y direction is increased by coordinate conversion, while the base line length tx in the x direction is decreased by coordinate conversion. Therefore, the influence of the error of the parallax dx ′ in the x ′ direction after the coordinate conversion on the calculation result of the three-dimensional coordinates on the subject is larger than that before the coordinate conversion. Therefore, the external parameter calculation unit 305 may calculate the three-dimensional coordinates on the subject without performing coordinate conversion with respect to the x direction having the long baseline length tx. This prevents the influence of the x-direction parallax dx error on the x-coordinate of the point on the subject from being increased by coordinate conversion, while giving the y-direction parallax dy error to the y-coordinate of the point on the subject. The influence can be reduced by coordinate transformation, which is preferable.

As described above, in the present embodiment, when the baseline length ty in the y direction is short, the external parameter calculation unit 305 performs coordinate conversion so that the short baseline length ty is long and the parallax dy is enlarged. Then, after coordinate transformation to calculate the distance D _stereo on the object to be measured based on an image, the external parameters that minimize the difference delta _D between the actual distance D _real. Thereby, even when the parallaxes dx and dy include an error, the influence of the error on the calculation result of the three-dimensional coordinates on the subject can be reduced. Therefore, all external parameters can be calculated with high accuracy.

[Third Embodiment]
Another embodiment of the present invention will be described. For convenience of explanation, members having the same functions as those described in the embodiment are given the same reference numerals, and descriptions thereof are omitted.

  As described in the second embodiment, when the baseline length ty in the y direction is short and the parallax dy is small, the parallax dy error greatly affects the calculation result of the three-dimensional coordinates on the subject.

  Therefore, in the present embodiment, the parallax dy related to the y direction with the short baseline length ty is used as an evaluation value, and the external parameter calculation unit 305 evaluates an error of the parallax dy as an evaluation value (second evaluation step). Thereby, it is possible to suppress the error of the parallax dy from having a great influence on the calculation result of the three-dimensional coordinates on the subject.

  Using the equation (36), the z coordinate Z1401 of the point on the subject corresponding to the feature point is calculated using the parallax in the x direction, and the estimated value of the parallax dy in the y direction is calculated from the calculated Z1401. The parallax dy is

It is represented by When the external parameter is correct, the estimated value of the parallax dy calculated from the equations (36) and (52) is equal to the parallax dy calculated from the image. Therefore, in the present embodiment, the external parameter calculation unit 305 uses the first parallax to calculate two points on the subject measured based on the three-dimensional coordinates on the subject calculated from the equations (36), (37), and (38). And the actual distance between two points on the subject (first evaluation value) and the three-dimensional coordinates on the subject calculated from the equation (36) using the first parallax. The external parameter ty is calculated so as to minimize the difference (second evaluation value) between the estimated value of the parallax dy calculated from the equation (52) and the parallax dy in the y direction calculated from the image. For example, the evaluation value Δ is calculated using a constant k, an error Δ _d of a distance between two points on the subject measured using parallax in the x direction, and an error Δ _{disparity_y} of parallax dy in the y direction,

It is represented by Here, the constant k is the weight (magnitude) of the error Δ _d of the distance between two points on the subject measured using the parallax in the x direction and the weight (magnitude) of the error Δ _{disparity_y} of the parallax dy in the y direction. It may be set so that the difference from) becomes smaller.

  As described above, in this embodiment, when the baseline length tx in the x direction is long and the baseline length ty in the y direction is short, the external parameter calculation unit 305 determines the second feature point based on the parallax dx in the x direction. The z-coordinate of the corresponding point on the subject is calculated, and the assumed parallax dy in the y direction is calculated from the calculated z-coordinate. The difference between the calculated y-direction parallax and the y-direction parallax on the rectified stereo image, and the difference between the measured distance based on the x-direction parallax and the actual distance are minimized. Calculate external parameters. Thereby, all the external parameters can be calculated with high accuracy.

  Note that the above-described camera calibration may be realized by a computer. In that case, the program for realizing the above-described camera calibration may be recorded on a computer-readable recording medium, and the program recorded on the recording medium may be read into a computer system and executed. The “computer-readable recording medium” here refers to a storage device such as a flexible disk, a magneto-optical disk, a portable medium such as a ROM or a CD-ROM, and a hard disk built in a computer system. Furthermore, the “computer-readable recording medium” is a medium that dynamically holds a program for a short time, such as a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line, In such a case, a volatile memory inside a computer system serving as a server or a client may be included and a program that holds a program for a certain period of time. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

  Further, part or all of the camera calibration in the above-described embodiment may be realized as an integrated circuit such as an LSI (Large Scale Integration). Each functional block of camera calibration may be individually made into a processor, or a part or all of them may be integrated into a processor. Further, the method of circuit integration is not limited to LSI, and may be realized by a dedicated circuit or a general-purpose processor. Further, in the case where an integrated circuit technology that replaces LSI appears due to progress in semiconductor technology, an integrated circuit based on the technology may be used.

  As described above, the embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to the above, and various design changes and the like can be made without departing from the scope of the present invention. It is possible to

[Example of software implementation]
The control device 300 (especially the external parameter calculation unit 305) of the stereo camera system 1 may be realized by a logic circuit (hardware) formed in an integrated circuit (IC chip) or the like, or a CPU (Central Processing Unit). And may be realized by software.

  In the latter case, the stereo camera system 1 includes a CPU that executes instructions of a program that is software that implements each function, and a ROM (Read Only Memory) in which the program and various data are recorded so as to be readable by a computer (or CPU). Alternatively, a storage device (these are referred to as “recording media”), a RAM (Random Access Memory) that expands the program, and the like are provided. And the objective of this invention is achieved when a computer (or CPU) reads the said program from the said recording medium and runs it. As the recording medium, a “non-temporary tangible medium” such as a tape, a disk, a card, a semiconductor memory, a programmable logic circuit, or the like can be used. The program may be supplied to the computer via an arbitrary transmission medium (such as a communication network or a broadcast wave) that can transmit the program. The present invention can also be realized in the form of a data signal embedded in a carrier wave in which the program is embodied by electronic transmission.

[Summary]
A camera calibration method according to aspect 1 of the present invention is a camera calibration method for calculating camera parameters of a stereo camera from a stereo image obtained by imaging a subject with a stereo camera,
A distance between two points on the subject corresponding to two points on the stereo image calculated based on a first parallax that is a parallax between the stereo images in a first direction of the stereo camera; A first evaluation step for calculating a first evaluation value that is a difference from an actual distance between the two points;
A second evaluation step of calculating a second evaluation value based on a second parallax that is a parallax between the stereo images in a second direction different from the first direction;
And a calibration step for calculating the camera parameter so as to minimize the first evaluation value and the second evaluation value.

  According to the above configuration, in calculating the camera parameter of the stereo camera, in addition to the first evaluation value of the distance based on the parallax in the first direction, the second direction (different from the first direction) The second evaluation value based on the parallax at is also taken into account. Therefore, the camera parameters can be calculated with higher accuracy than the camera calibration method that calculates the camera parameters based only on the evaluation value based on the parallax in a single direction.

  The camera calibration method according to aspect 2 of the present invention is the camera calibration method according to aspect 1, in which the second evaluation step is performed between two points on the subject corresponding to two points on the image calculated based on the second parallax. And the actual distance between two points on the subject may be calculated as the second evaluation value.

  According to the above configuration, based on the first evaluation value that is the difference between the distance between the two points calculated based on the first parallax and the actual distance between the two points, and the second parallax. The camera parameter is calculated so as to minimize the second evaluation value that is the difference between the calculated distance between the two points and the actual distance between the two points. Therefore, the camera parameters can be calculated with higher accuracy than the camera calibration method that calculates the camera parameters based only on the parallax measurement in a single direction.

  In the camera calibration method according to aspect 3 of the present invention, in the above aspect 1, the second evaluation step includes the second parallax and the estimated value of the second parallax calculated based on the first parallax. May be calculated as the second evaluation value.

  According to the above configuration, the first evaluation value that is the difference between the distance between the two points calculated based on the first parallax and the actual distance between the two points, the second parallax, The camera parameters are calculated so as to minimize the difference from the estimated value of the second parallax calculated based on the first parallax. Therefore, even when the second parallax is small, the camera parameters can be calculated with higher accuracy.

  A camera calibration method according to aspect 4 of the present invention includes a coordinate conversion step of performing coordinate conversion so as to increase a smaller one of the first parallax and the second parallax in the first to third aspects. The camera parameters may be calculated from the stereo image coordinate-converted in the coordinate conversion step.

  According to the above configuration, for example, by rotating at least one of the first direction and the second direction, the smaller one of the first parallax and the second parallax increases. In the distance measurement method based on parallax, the larger the parallax is, the less influence the fluctuation (error) of parallax has on the distance measurement result. Therefore, according to the above configuration, the camera parameters can be calculated with higher accuracy.

  In the camera calibration method according to aspect 5 of the present invention, in the above aspects 1 to 4, the camera parameter may be an external parameter of the stereo camera.

  According to said structure, the measurement accuracy of the distance by a camera system can be improved by calculating an external parameter.

  The camera calibration method according to Aspect 6 of the present invention includes the image parallax extraction step of extracting a specific image area with less lens distortion of the stereo camera from the stereo image according to the aspects 1 to 5, wherein the first parallax is provided. The second parallax may be a parallax in the specific image area extracted in the image area extraction step.

  According to the above configuration, the first parallax and the second parallax are parallaxes in an image region without distortion based on lens aberration. Therefore, it is possible to calculate the distance between the two points and the measurement error thereof based on the first parallax and the second parallax without considering image distortion.

  A program for realizing the camera calibration method according to each aspect of the present invention on a computer and a computer-readable recording medium on which the program is recorded also fall within the scope of the present invention.

[Another aspect of the present invention]
According to one aspect of the present invention, the distance between two points in the stereo image is calculated from the three-dimensional coordinates based on the parallax in the direction in which the base line length of the stereo camera that captured the stereo image is long, and the actual distance between the two points. And calculating a camera parameter that minimizes an evaluation value based on a parallax in a direction with a short baseline length.

  In another aspect of the present invention, the evaluation value based on the parallax in the direction with the short base length is calculated by calculating the distance of the subject from the three-dimensional coordinates based on the parallax in the direction with the short base length, and the known distance. It is a difference from the distance.

  In another aspect of the present invention, the coordinate conversion is performed so that the parallax in the direction in which the baseline length is short increases, and the distance of the subject is calculated from the three-dimensional coordinates based on the parallax after the coordinate conversion in the direction in which the baseline length is long. A difference between the distance and the known distance is minimized, a measurement distance obtained by calculating the distance of the subject from three-dimensional coordinates based on the parallax after coordinate conversion in a direction in which the baseline length is short, and the known distance The camera parameter that minimizes the difference is calculated.

  In another aspect of the present invention, the evaluation value based on the parallax in the direction in which the baseline length is short is calculated based on the three-dimensional coordinates calculated based on the parallax in the direction in which the baseline length is long. And a parallax in a direction with a shorter baseline length calculated from the stereo image.

  In another aspect of the present invention, the internal parameters are calculated independently, and the distance between two points in the stereo image is calculated from the three-dimensional coordinates based on the parallax in the direction in which the baseline length of the stereo camera that captured the stereo image is long. An external parameter for minimizing a difference between the distance and an actual distance between the two points and minimizing an evaluation value based on a parallax in a direction with a short base line length is calculated.

  In another aspect of the present invention, an internal parameter is calculated independently, and the evaluation value based on the parallax in the direction with the short base length calculates the distance of the subject from the three-dimensional coordinates based on the parallax in the direction with the short base length The difference between the measured distance and the known distance.

  According to another aspect of the present invention, internal parameters are independently calculated, coordinate conversion is performed so that the parallax in the direction in which the baseline length is short is increased, and the three-dimensional coordinates based on the parallax after coordinate conversion in the direction in which the baseline length is long Measurement that minimizes the difference between the measured distance obtained by calculating the distance of the subject and the known distance, and calculates the distance of the subject from three-dimensional coordinates based on the parallax after coordinate conversion in the direction in which the baseline length is short. A camera parameter that minimizes a difference between a distance and the known distance is calculated.

  In another aspect of the present invention, internal parameters are calculated independently, and the evaluation value based on the parallax in the direction with the shorter baseline length is calculated based on the three-dimensional coordinates calculated based on the parallax in the direction with the longer baseline length. The difference between the parallax in the direction in which the baseline length is short and the parallax in the direction in which the baseline length calculated from the stereo image is short is characterized.

  According to another aspect of the present invention, an internal parameter is calculated independently, a feature point selection region is limited based on a distortion correction result at the time of calculating the internal parameter, and based on a feature point coordinate selected from the feature point selection region. Another parameter is calculated.

  The present invention can be used for camera parameter calibration.

1 Stereo camera system (camera system)
200a, 200b Imaging device (camera)
201 Calibrator (Subject)

Claims (4)

A measurement device that performs measurement based on a stereo image obtained by imaging a subject with a stereo camera,
A first parallax between the stereo images in a first direction parallel to the baseline direction of the stereo camera when the calibrator is imaged, and between the stereo images in a second direction orthogonal to the baseline direction A calibration unit that calibrates the measurement device with reference to the second parallax ,
The calibration unit, the first parallax and of the second parallax measuring features that you calculate the external camera parameters from the stereo images obtained by the coordinate transformation to increase the smaller parallax device. An image area extraction unit that extracts a specific image area with less lens distortion of the stereo camera from the stereo image,
The calibration unit refers to the parallax in the specific image region between the stereo images in the first direction and the parallax in the specific image region between the stereo images in the second direction, and the measurement device The measuring apparatus according to claim 1, wherein A method for calibrating a measurement device that performs measurement based on a stereo image obtained by imaging a subject with a stereo camera,
A first parallax between the stereo images in a first direction parallel to the baseline direction of the stereo camera when the calibrator is imaged, and between the stereo images in a second direction orthogonal to the baseline direction A calibration step of calibrating the measurement device with reference to a second parallax ;
In the calibration step, an external camera parameter is calculated from the stereo image coordinate-transformed so as to increase a smaller one of the first parallax and the second parallax .   A calibration program for causing a computer to function as the calibration unit of the measuring apparatus according to claim 1, wherein the calibration program is for causing the computer to function as the calibration unit.

Images