JP2008112412A - Data processing device, data processing method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To increase the speed in searching for the closest point in a surface of a three-dimensional model. <P>SOLUTION: Concerning the three-dimensional model constition parts that constitute a three-dimensional model, the surface of a three-dimensional model consisting of a triangle v<SB>i</SB>c<SB>0</SB>v<SB>i+1</SB>obtained by equally dividing the lower bottom face into six parts, a side surface v<SB>i</SB>v<SB>i+1</SB>v<SB>i+1</SB>'v<SB>i</SB>' and a triangle v<SB>i</SB>'c<SB>0</SB>'v<SB>i+1</SB>' obtained by equally dividing the upper bottom face into six parts is specified as a region the closest point is searched. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a data processing apparatus, a data processing method, and a program for tracking the position and orientation of a target object such as a person and constructing a three-dimensional model.

  2. Description of the Related Art Conventionally, there is a data processing technique for building a three-dimensional model that tracks the motion of a target object by measuring the surface of the target object such as a person using a sensor or the like and reproduces the motion of the target object. In such a data processing technique, in order to completely reproduce the operation of the target object, a distance image representing the surface shape of the target object as a distance from the measurement position of the sensor is acquired from a plurality of directions with respect to the target object.

  A plurality of distance images acquired from a plurality of directions are described in a coordinate system indicating each measurement position, and an alignment process is required to obtain a relative position and orientation of each and unify the coordinate system.

  In order to solve this distance image alignment problem, for example, as shown in Non-Patent Document 1, there is a method of applying an ICP (Iterative Closest Point) algorithm.

  The ICP algorithm calculates a rigid body transformation parameter that minimizes an error between corresponding points indicating the quality of the corresponding state between data by iterative calculation.

  When the ICP algorithm is used for such a data processing technique, the nearest neighbor point in two distance images is used as a corresponding point, and a transformation matrix of each distance image is repeatedly calculated so as to minimize an error between the corresponding points. The relative position is specified by.

P. J Besl, and N.J. D. McKay; “A method for registration of 3-D shapes,” IEEE Trans. of PAMI, vol. 14, no. 2, pp. 239-256 (1992)

  However, since the processing operation based on the ICP algorithm requires a long time, there is a problem that real-time application is difficult. In the ICP algorithm, the amount of calculation in the process of searching for the nearest point on the surface of the three-dimensional model is large, and the time required for this calculation process also becomes long.

  The present invention has been proposed in view of such a conventional situation, and an object of the present invention is to provide a data processing device, a data processing method, and a program capable of speeding up the nearest neighbor search process. .

  In order to achieve the above-described object, a data processing apparatus according to the present invention is a data processing apparatus that projects a three-dimensional position of a target object onto a three-dimensional model composed of components having a polygonal bottom surface. A three-dimensional surface generating means for generating a three-dimensional surface, and the distance from the three-dimensional point indicating a predetermined position on the three-dimensional surface of the target object to the surface of the constituent part is the shortest on the surface of the constituent part. Nearest neighbor point search area specifying means for specifying an area for searching for a neighboring point; nearest neighbor point search means for searching for the nearest neighbor point in each plane constituting the area specified by the nearest neighbor point search area specifying means; The nearest point that outputs the nearest point that has the shortest distance from the three-dimensional point among the plurality of nearest points searched by the neighbor search means And calculating the transformation matrix that minimizes the error function in the distance from the nearest point output from the nearest point output means to the three-dimensional point corresponding to the nearest point, and the nearest point and the three-dimensional A transformation matrix calculating means for specifying a relative position with respect to the point, and the three-dimensional point corresponding to the three-dimensional point based on a relative position between the nearest neighbor point specified by the conversion matrix calculating means and the three-dimensional point. 3D model movement processing means for projecting to the position of the nearest neighbor point and moving the 3D model.

  In order to achieve the above-described object, the data processing method according to the present invention is a data processing method for projecting a three-dimensional position of a target object onto a three-dimensional model composed of components having a polygonal bottom surface. A three-dimensional surface generating step for generating a three-dimensional surface of the object, and a distance from a three-dimensional point indicating a predetermined position on the three-dimensional surface of the target object to the surface of the constituent part on the surface of the constituent part is the shortest A nearest point search region specifying step for specifying a region for searching for the nearest point, and a nearest point search step for searching for the nearest point in each plane constituting the region specified in the nearest point search region specifying step, The nearest neighbor point output that outputs the nearest neighbor point having the shortest distance from the three-dimensional point among the plurality of nearest neighbor points searched in the nearest neighbor point search step. And calculating a transformation matrix that minimizes an error function in the distance from the nearest neighbor point output in the nearest neighbor point output step to the three-dimensional point corresponding to the nearest neighbor point, and the nearest neighbor point and the three-dimensional A transformation matrix calculating step for specifying a relative position with respect to the point, and the three-dimensional point corresponding to the three-dimensional point based on a relative position between the nearest point specified in the transformation matrix calculating step and the three-dimensional point And a three-dimensional model movement processing step of projecting to the position of the nearest point to be moved and moving the three-dimensional model.

  A program according to the present invention causes a computer to execute the data processing described above.

  According to the present invention, it is possible to speed up the process of searching for the nearest point on the surface of the three-dimensional model.

  Hereinafter, specific embodiments to which the present invention is applied will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram showing a configuration of a data processing apparatus 1 according to an embodiment of the present invention. The data processing apparatus 1 includes a camera 11R, a camera 11L, a three-dimensional surface generation unit 12, a nearest neighbor point search region specifying unit 13, a nearest neighbor point search unit 14, a nearest neighbor point output unit 15, and a transformation matrix calculation unit 16. A three-dimensional model movement processing unit 17 and a storage unit 18 are provided. The processing operation of the data processing device 1 is controlled by a CPU (Central Processing Unit) executing a program stored in a ROM (Read Only Memory) on a RAM (Random Access Memory).

  FIG. 2 is a diagram showing an outline of processing steps of the data processing apparatus 1. In the data processing apparatus 1, the three-dimensional model 23 is moved based on the three-dimensional surface 22 of the target object 21A.

  The camera 11R and the camera 11L, for example, photograph the target object 21A such as a person from the right direction and the left direction, respectively, and obtain a parallax image 21 based on the parallax between the camera 11R and the camera 11L.

  The three-dimensional surface generation unit 12 generates three-dimensional coordinates (hereinafter, referred to as a three-dimensional point) representing the three-dimensional surface 22 of the target object 21A based on the parallax images 21 obtained by the cameras 11R and 11L. The three-dimensional surface data composed of the three-dimensional points is supplied to the nearest point search area specifying unit 13.

  In the data processing apparatus 1, the three-dimensional model 23 is moved based on the three-dimensional surface data. The three-dimensional model 23 is configured by combining a plurality of constituent parts (hereinafter referred to as three-dimensional model constituent parts) whose shapes are a polygonal column, a polygonal pyramid, a polygonal frustum, and the like. The shape of the three-dimensional model constituent part may be any of a polygonal column, a polygonal frustum, and a polygonal pyramid, but in this embodiment, the shape of the three-dimensional model constituent part 23A having a regular hexagonal column is taken as an example. I will give you a description.

  The nearest neighbor search area specifying unit 13 divides the surface of the three-dimensional model constituent part 23A into predetermined areas, thereby obtaining a distance from the three-dimensional point to the three-dimensional model constituent part 23A on the surface of the three-dimensional model constituent part 23A. An area (hereinafter referred to as the nearest neighbor search area) for searching for the minimum point (hereinafter referred to as the nearest neighbor point) is specified.

  The storage unit 18 stores predetermined data of the three-dimensional model 23 such as three-dimensional coordinates indicating the position of the three-dimensional model 23 in units of frames. The nearest neighbor search unit 14 reads predetermined data of the three-dimensional model 23 in a specific frame from the storage unit 18 and performs a search process of the nearest point on each of a plurality of planes constituting the nearest neighbor search region.

  The nearest neighbor point output unit 15 outputs the nearest point that minimizes the distance from the three-dimensional point to the plurality of nearest points searched by the nearest point search unit 14.

  The transformation matrix calculation unit 16 calculates a transformation matrix that minimizes the error function in the distance between the nearest point output from the nearest point output unit 15 and the three-dimensional point corresponding to the nearest point, and the error function is predetermined. The calculation is repeated until the threshold value becomes smaller than the threshold value, and the relative position between the target object 21A and the three-dimensional model component 23A is specified.

  The three-dimensional model movement processing unit 17 projects the three-dimensional point to the position of the nearest neighbor point based on the relative position between the three-dimensional point specified by the transformation matrix calculation unit 16 and the nearest point, and a plurality of the three-dimensional model movement processing unit 17 for each frame. The three-dimensional model 23 composed of the three-dimensional model constituent part 23A is moved.

  Here, the processing operation of the data processing apparatus 1 will be described in detail with reference to the flowchart of FIG. The data processing apparatus 1 applies an ICP (Iterative Closest Point) algorithm to minimize the distance from the three-dimensional point to the three-dimensional model component part 23A in the parallax images in frame units obtained by the camera 11R and the camera 11L. A three-dimensional model 23 is moved by calculating a relative position between the target object 21A and the three-dimensional model constituent part 23A by calculating a transformation matrix of each parallax image and repeatedly performing the calculation.

  In step S1, the three-dimensional surface generation unit 12 generates three-dimensional surface data including three-dimensional points representing the three-dimensional surface 22 of the target object 21A using the parallax images 21 obtained by the cameras 11R and 11L. The three-dimensional surface data is supplied to the nearest point search area specifying unit 13.

  In step S2, the nearest neighbor point search area specifying unit 13, the nearest neighbor point searching unit 14, and the nearest point output unit 15 perform the processing operations from step S21 to step S29 shown in the flowchart of FIG. The nearest neighbor point having the shortest distance from the predetermined three-dimensional point on the surface to the three-dimensional model constituent part 23 </ b> A is generated, and this nearest neighbor point is output to the transformation matrix calculation unit 16.

In step S21, nearest neighbor search area specifying unit 13, as shown in FIG. 5, the vector p indicates the three-dimensional point, the vector c ₀ indicating the center point of the bottom surface of a 3D model construction site 23A, three-dimensional A unit projection vector n _p that is a vector for specifying a region for searching for the nearest neighbor point in the three-dimensional model component part 23A using the normal vector n _{c on} the lower bottom surface of the model component part 23A is expressed by the following equation. Calculated according to (1).

In step S22, as shown in FIG. 6, the nearest neighbor point search region specifying unit 13 sets the angle θ obtained by the unit projection vector n _p and the angle start vector n _v indicating the start direction of the angle to the following formula (2). Calculated by

  The angle θ can take both a positive value and a negative value. In the following formula (3), a positive value is obtained when z is greater than 0, and a negative value is obtained when z is 0 or less. Takes the value of

In FIG. 6, theta _{(v i)} is the angle obtained by the vertex vectors _{v i} representing the angular starting vector _{n v} and the vertex _{v i,} theta _{(v i + 1),} the angle starting vector _{n v} and the vertex _{v i + 1} And an angle obtained by a vertex vector v _{i + 1} representing.

In step S23, the nearest point search area specifying unit 13 specifies an area for performing the nearest neighbor search process on the surface of the three-dimensional model constituent part 23A based on the angle θ calculated in step S22. That is, when the angle θ satisfies θ (v _i ) <θ <θ (v _{i + 1} ), the nearest neighbor point search region specifying unit 13 obtains a triangle obtained by dividing the lower bottom surface into six equal parts as shown in FIG. A three-dimensional model surface composed of v _i c ₀ v _{i + 1} , side face v _i v _{i + 1} v _{i + 1} 'v _i ', and triangle v _i 'c ₀ ' v _{i + 1} 'obtained by dividing the upper base into six equal parts. It is assumed that the nearest neighbor search process is performed in the model component part 23A. Regions 3D points can exist for performing search processing nearest neighbor in the three-dimensional model surface, as shown in Figure 8, a triangular prism _{v i c 0 v i + 1} v i 'c 0' v i + 1 ' It becomes an area obtained by enlarging.

In this embodiment, when the shape of the three-dimensional model component is, for example, a regular hexagonal pyramid as shown in FIG. 9A or a regular hexagonal pyramid as shown in FIG. The three-dimensional model surfaces for performing the search process are triangles v _j c _a v _{j + 1} , side surfaces v _j v _{j + 1} v _{j + 1} 'v _j ' and triangles v _j 'c _a v as shown in FIG. _{j + 1} becomes "3-dimensional model surface consisting a, 10 a triangle as shown in _{(B) v k c b v} k + 1 and the side surface _{v k c b 'v k +} 1 Metropolitan 3-dimensional model surface made. In addition, regions where a 3D point for performing the nearest neighbor search process on the surface of the 3D model shown in FIGS. 10A and 10B can exist are as shown in FIG. 11A. An area in which the triangular pyramid is enlarged is an area in which the triangular pyramid is enlarged as shown in FIG.

In step S24, the nearest point search unit 14 searches for the nearest point on the lower bottom surface of the three-dimensional model component 23A. In this step S24, first, the nearest point searching unit 14 obtains a triangle obtained by dividing the lower bottom surface into six equal parts by the three-dimensional point indicated by the vector p when the three-dimensional model constituent part 23A is viewed from the lower bottom surface direction. It is determined by the following formula (4) whether or not it exists inside v _i c ₀ v _{i + 1} .

The nearest neighbor search unit 14 determines that the three-dimensional point indicated by the vector p exists outside the triangle v _i c ₀ v _{i + 1} when 0 <in in this equation (4). 5) and equation (6) recently point indicated by the vector p _c which is calculated by the neighbor.

  The nearest point searching unit 14 calculates a distance from the three-dimensional point to the nearest point, and supplies the distance and the three-dimensional coordinates of the nearest point to the nearest point output unit 15.

On the other hand, if it is in <0 In this equation (4), nearest neighbor searching unit 14 determines that the three-dimensional point indicated by the vector p is present inside the triangle _{v i c 0 v i + 1} , the following equation ( The point indicated by the vector p _j calculated by 7) and Equation (8) is set as the nearest point. Note that the nearest point indicated by the vector p _j is located at the intersection of the perpendicular line drawn from the three-dimensional point to the lower bottom surface of the three-dimensional model constituent part 23A and the lower bottom surface.

  The nearest point searching unit 14 calculates a distance from the three-dimensional point to the nearest point, and supplies the distance and the three-dimensional coordinates of the nearest point to the nearest point output unit 15.

In step S25, the nearest point search unit 14 searches for the nearest point on the side surface of the three-dimensional model component 23A. In this step S25, first, the nearest neighbor searching unit 14 finds that the three-dimensional point indicated by the vector p when the three-dimensional model component part 23A is viewed from the side direction is the inside of the side surface v _i v _{i + 1} v _{i + 1} 'v _i '. Is determined by the following formulas (9) to (12).

The nearest neighbor searching unit 14 determines that the three-dimensional point indicated by the vector p is the side face v _i v _{i + 1} v _{i + 1} ′ when 0 <in ₁ , 0 <in ₂ , 0 <in ₃ , or 0 <in _4. It is determined that it exists outside v _i ′.

That is, if it is 0 <in ₁ In Equation (9), nearest neighbor search unit 14, and a point indicated by the vector p _c which is calculated by the equation (6) nearest neighbor.

Also, if it is 0 <in ₂ in equation (10), nearest neighbor searching unit 14, the points represented by the vector _{p c} calculated by the following equation (13) and Equation (14) recently a neighbor.

Also, if it is 0 <in ₃ In Equation (11), nearest neighbor searching unit 14, the points represented by the vector _{p c} calculated by the following equation (15) and Equation (16) recently a neighbor.

Also, if it is 0 <in ₄ in Equation (12), nearest neighbor searching unit 14, the points represented by the vector _{p c} calculated by the following equation (17) and Equation (18) recently a neighbor.

On the other hand, when in ₁ <0 and in ₂ <0 and in ₃ <0 and in ₄ <0, the nearest neighbor search unit 14 determines that the three-dimensional point indicated by the vector p is the side surface v _i v _{i + 1} v _{i + 1} 'v. _It is determined that it exists inside _i ′, and the point indicated by the vector p _j calculated by the following equations (19) and (20) is set as the nearest neighbor point. Note that the nearest point indicated by the vector p _j is located at the intersection of the perpendicular line and the side surface, which extends from the three-dimensional point to the side surface of the three-dimensional model constituent part 23A.

  The nearest point searching unit 14 calculates a distance from the three-dimensional point to the nearest point, and supplies the distance and the three-dimensional coordinates of the nearest point to the nearest point output unit 15.

  In step S26, the nearest neighbor point search unit 14 determines whether or not the shape of the three-dimensional model 23 is a cone such as a regular hexagonal pyramid. In step S26, if the shape of the three-dimensional model 23 is any cone, the process proceeds to step S28, and if not, the process proceeds to step S27.

When the shape of the three-dimensional model is not a cone, in step S27, the nearest point search unit 14 searches for the nearest point on the upper bottom surface of the three-dimensional model component 23A. In this step S27, first, the nearest point searching unit 14 obtains a triangle obtained by dividing the upper bottom surface into six equal parts by the three-dimensional point indicated by the vector p when the three-dimensional model constituent part 23A is viewed from the upper bottom surface direction. It is determined by the following formula (21) whether or not it exists inside v _i 'c ₀ v _{i + 1} '.

The nearest neighbor search unit 14 determines that the three-dimensional point indicated by the vector p exists inside the triangle v _i 'c ₀ v _{i + 1} ' if in <0 in Equation (21), The point indicated by the vector p _j calculated by (22) and Equation (23) is set as the nearest point.

On the other hand, when 0 <in in Equation (21), the nearest neighbor point search unit 14 determines that the three-dimensional point indicated by the vector p exists outside the triangle v _i 'c ₀ v _{i + 1} '. 13) and equation (14) recently point indicated by the vector p _c which is calculated by the neighbor.

  The nearest point searching unit 14 calculates a distance from the three-dimensional point to the nearest point, and supplies the distance and the three-dimensional coordinates of the nearest point to the nearest point output unit 15.

  When the shape of the three-dimensional model component 23A is a cone, in step S28, the nearest neighbor point search unit 14 calculates the distance from the three-dimensional point to the nearest point by setting the vertex of the cone as the nearest point. The distance and the three-dimensional coordinates of the nearest point are supplied to the nearest point output unit 15.

  In step S29, the nearest neighbor point output unit 15 converts the nearest neighbor point having the shortest distance from the three-dimensional point to the nearest neighbor point among the nearest neighbor points calculated in step S24, step S25, and step S27 or step S28. The result is output to the calculation unit 16.

  Returning to FIG. 3, in step S <b> 3, the transformation matrix calculation unit 16 calculates a transformation matrix that minimizes the error function in the distance from the nearest point output from the nearest point output unit 15 to the corresponding three-dimensional point.

  In step S4, the transformation matrix calculation unit 16 determines whether or not the error function in the distance from the nearest point output from the nearest point output unit 15 to the corresponding three-dimensional point is smaller than a predetermined threshold value. In step S4, when the error function is smaller than the predetermined threshold value, the process proceeds to step S5. On the other hand, if the error function is greater than or equal to the predetermined threshold value in step S4, the process returns to step S2, and the processing operations in steps S2 to S4 are repeated until the error function becomes smaller than the predetermined threshold value. The relative position between the three-dimensional point and the nearest point is specified by the processing operations in steps S2 to S4.

  In step S5, the three-dimensional model movement processing unit 17 projects the three-dimensional point to the position of the corresponding nearest point based on the relative position between the three-dimensional point specified by the transformation matrix calculation unit 15 and the nearest point, The 3D model 23 composed of a plurality of 3D model components 23A is moved every time.

  Table 1 below shows the time required for the nearest point search process performed on the surface of the three-dimensional model constituent part when approximating the three-dimensional model constituent part of the regular hexagonal column to a cylinder, and the three-dimensional model constituent part of the regular pentagonal prism The time required for the nearest neighbor search process performed on the surface of the three-dimensional model component when approximating a cylinder to the nearest neighbor search process by the conventional Octtree Subdivision and the present embodiment The result compared with the nearest neighbor search process is shown.

  As can be seen from Table 1, in the data processing apparatus 1, the time required for the nearest neighbor search process is the case where the shape of the three-dimensional model component is a regular hexagonal cylinder with respect to the time required for the nearest neighbor search process by the Octtree Subdivision Was about 0.062 times, and when the shape of the three-dimensional model constituent part was a regular pentagonal prism, it was about 0.038 times.

  In addition, as can be seen from Table 1, the time required for the nearest point search processing performed when approximating a three-dimensional model component of a regular pentagonal column to a cylinder approximates the three-dimensional model component of a regular hexagonal column to a cylinder. The nearest neighbor point search process by the Octtree Subdivision is about 1.693 times the time required for the nearest neighbor point search process to be performed, but the nearest neighbor point search process in the data processing apparatus 1 is about 1.033 times. It was.

  That is, in the nearest neighbor search process by the data processing device 1, the processing time is significantly shortened as compared with the nearest neighbor search process by the Octtree Subdivision which has been conventionally performed. Further, in the nearest point search process by the data processing device 1, when the shape of the bottom surface of the three-dimensional model component is a regular n prism (n = 3, 4, 5,...), The value of n is set. Even if it is greatly increased, the rate of increase in time required for nearest neighbor search processing remains small compared with the rate of increase in time required for nearest neighbor search by Octree Subdivision.

  As described above, in the data processing apparatus 1 according to the embodiment to which the present invention is applied, the three-dimensional model is searched in the nearest point search process performed when the three-dimensional model is constructed based on the three-dimensional surface of the target object. Since the search area for the nearest point on the surface is specified as a predetermined area, it is possible to speed up the search process for the nearest point compared to the conventional technique.

  Further, in the data processing apparatus 1, the calculation amount in the nearest point search process is not significantly increased even in the complicated shape of the three-dimensional model compared to the simple shape of the three-dimensional model, and the processing speed is higher than the conventional one. Can be realized.

  In addition, the data processing apparatus 1 according to an embodiment to which the present invention is applied can be applied to various apparatuses used in the industry. For example, the data processing device 1 can be applied to a motion capture device that records a movement of a target object by combining a marker attached to the target object and a tracker that detects the marker. Further, for example, the data processing device 1 can be applied to a medical device that models a three-dimensional surface of a bone measured by X-ray or the like into a three-dimensional model whose shape is any polygonal column.

  It should be noted that the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the scope of the present invention.

It is a figure which shows the structure of the data processor in one Embodiment to which this invention is applied. It is a figure which shows the outline | summary of the process process of the data processor in one Embodiment to which this invention is applied. It is a flowchart for demonstrating the processing operation of the data processor in one Embodiment to which this invention is applied. It is a flowchart for demonstrating the nearest point search process of the data processor in one Embodiment to which this invention is applied. It is a figure which shows a mode that it projects on the lower bottom face of a three-dimensional model structure site | part from a three-dimensional point. It is a figure for demonstrating the calculation process of the angle obtained by a unit projection vector and an angle start vector. It is a figure which shows the area | region where a nearest neighbor point can exist. It is a figure which shows the area | region in which a three-dimensional point can exist. It is a figure which shows the example of the shape of a three-dimensional model structure site | part. It is a figure which shows the area | region where a nearest neighbor point can exist. It is a figure which shows the area | region in which a three-dimensional point can exist.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Data processing apparatus, 11R, 11L camera, 12 3D surface production | generation part, 13 Nearest neighbor search area specific | specification part, 14 Nearest neighbor search part, 15 Nearest neighbor output part, 16 Transformation matrix calculation part, 17 3D model movement process part , 18 Memory unit

Claims (6)

In a data processing apparatus for projecting a three-dimensional position of a target object onto a three-dimensional model composed of components having a polygonal bottom surface,
3D surface generation means for generating a 3D surface of the target object;
On the surface of the component part, a nearest neighbor point search region specification that specifies a region for searching for the nearest point having the shortest distance from the three-dimensional point indicating a predetermined position on the three-dimensional surface of the target object to the surface of the component part Means,
In each plane constituting the area specified by the nearest neighbor search area specifying means, nearest neighbor point searching means for searching for the nearest neighbor point, and
A nearest point output means for outputting a nearest point having the shortest distance from the three-dimensional point among the plurality of nearest points searched by the nearest point search means;
By calculating a transformation matrix that minimizes an error function in the distance from the nearest point output from the nearest point output means to the three-dimensional point corresponding to the nearest point, the relative between the nearest point and the three-dimensional point is calculated. Transformation matrix calculation means for specifying a position;
Based on the relative position between the nearest point specified by the transformation matrix calculation means and the three-dimensional point, the three-dimensional point is projected to the position of the nearest point corresponding to the three-dimensional point, and the three-dimensional model is moved. And a three-dimensional model movement processing means.   The data processing apparatus according to claim 1, wherein the shape of the constituent parts constituting the three-dimensional model is a polygonal column, a polygonal pyramid, or a polygonal pyramid.   The nearest-neighbor point search area specifying means is calculated from a vector indicating the three-dimensional point, a vector indicating the center point of the bottom surface, and a normal vector of the bottom surface on the bottom surface of the constituent part constituting the three-dimensional model. 2. The data processing apparatus according to claim 1, wherein a region for searching for the nearest point is specified based on a vector.   2. The data according to claim 1, wherein the transformation matrix calculation means specifies a relative position between the nearest neighbor point and the three-dimensional point by repeatedly calculating until the error function becomes smaller than a predetermined threshold value. Processing equipment. In a data processing method for projecting a three-dimensional position of a target object onto a three-dimensional model composed of components having a polygonal bottom surface,
A three-dimensional surface generation step of generating a three-dimensional surface of the target object;
On the surface of the component part, a nearest neighbor point search region specification that specifies a region for searching for the nearest point having the shortest distance from the three-dimensional point indicating a predetermined position on the three-dimensional surface of the target object to the surface of the component part Process,
In each plane constituting the area specified in the nearest point search area specifying step, the nearest point searching step for searching for the nearest point, respectively,
A nearest point output step of outputting a nearest point having the shortest distance from the three-dimensional point among the plurality of nearest points searched in the nearest point search step;
By calculating a transformation matrix that minimizes an error function in the distance from the nearest point output in the nearest point output step to the three-dimensional point corresponding to the nearest point, the nearest point and the three-dimensional point are calculated. A transformation matrix calculation step for specifying a relative position;
Based on the relative position between the nearest point specified in the transformation matrix calculation step and the three-dimensional point, the three-dimensional point is projected to the position of the nearest point corresponding to the three-dimensional point, and the three-dimensional model is A data processing method comprising: moving a three-dimensional model moving process step. A program for causing a computer to execute data processing for projecting a three-dimensional position of a target object onto a three-dimensional model composed of components having a polygonal bottom surface,
A three-dimensional surface generation step of generating a three-dimensional surface of the target object;
On the surface of the component part, a nearest neighbor point search region specification that specifies a region for searching for the nearest point having the shortest distance from the three-dimensional point indicating a predetermined position on the three-dimensional surface of the target object to the surface of the component part Process,
In each plane constituting the area specified in the nearest point search area specifying step, the nearest point searching step for searching for the nearest point, respectively,
A nearest point output step of outputting a nearest point having the shortest distance from the three-dimensional point among the plurality of nearest points searched in the nearest point search step;
By calculating a transformation matrix that minimizes an error function in the distance from the nearest point output in the nearest point output step to the three-dimensional point corresponding to the nearest point, the nearest point and the three-dimensional point are calculated. A transformation matrix calculation step for specifying a relative position;
Based on the relative position between the nearest point specified in the transformation matrix calculation step and the three-dimensional point, the three-dimensional point is projected to the position of the nearest point corresponding to the three-dimensional point, and the three-dimensional model is A program characterized by comprising a three-dimensional model movement processing step for moving.

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