JPH11259661A - Method and device for measuring moving picture speed field and recording medium where moving picture speed field measuring program is recorded - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide the method and device for moving picture field measurement which find the speed field of a moving picture fast and the recording medium where the moving picture speed field measuring program is recorded. SOLUTION: A time-series image is inputted (step 401), a partial image is extracted from a moving image (step 402), and a speed component in the partial image is estimated (step 403); and the possibility of the estimated speed (degree of contribution) is calculated as to respective pixels (step 404) and similar processes are performed for other partial images at different positions. After partial images covering the entire image area are all processed, speed components are put together by using the degrees of contribution to obtain the speed field of the whole image (step 406). Lastly, the speed field is outputted (step 407).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a technique for recognizing a motion of an object in a time-series image obtained by a video camera, a weather radar device, remote sensing, or the like.

[0002]

2. Description of the Related Art In monitoring of people, traffic and the like, controlling manufacturing processes, and elucidating and predicting natural phenomena such as weather, it is desired to improve the efficiency and efficiency of time-series image recognition processing.

Conventionally, there is a method using Hough transform (or voting) as a method for measuring the movement of an object from a time-series image. As an example, when considering a time-series image in which time-series images are stacked in the time direction, a curved motion trajectory drawn by an edge or contour of an object included in the image is detected, and a plurality of different motion trajectories in contact with the motion trajectory are detected. There is a method of obtaining the velocity component of an object from the direction of an intersection line formed by a tangent plane (Japanese Patent Application No. 9-214,197).
-3116, Japanese Patent Application No. 9-8563, Japanese Patent Application No. 9-11
No. 4577). This method converts a spatiotemporal image into a parameter space that expresses the velocity component (velocity method and size) of a target object by Hough transform, detects a peak of the distribution in the parameter space, and uses the coordinate values to determine the peak. The velocity component of the target object is obtained. This method has the advantage that the most dominant translation velocity component in the target area is obtained robustly against noise and occlusion.

[0004]

However, in the above-described conventional technique, when trying to obtain a velocity field of a moving image, it is necessary to cut out a partial image including its vicinity for each pixel and perform processing. In addition, the calculation cost is large,
There is a problem that processing time is long.

It is an object of the present invention to provide a moving image speed field measuring method and apparatus for obtaining a moving image speed field at a higher speed, and a recording medium on which a moving image speed field measuring program is recorded.

[0006]

A moving image speed field measuring method according to the present invention divides a moving image into a plurality of partial images overlapping each other, and estimates a dominant velocity component for each partial image. A step of calculating a degree having an estimated velocity component for each pixel in the partial image; a step of determining the presence or absence of a velocity component for each pixel in the partial image based on the magnitude of the degree; For each pixel included in the region where the images overlap each other and the pixel has a velocity component, and for a pixel for which a plurality of velocity components have been estimated, the velocity component is calculated using the degree having the plurality of velocity components. Is determined.

According to the moving image speed field measuring apparatus of the present invention, there are provided means for dividing a moving image into a plurality of partial images overlapping each other, means for estimating a dominant speed component for each partial image, Means for calculating the degree of the estimated velocity component for each pixel, means for determining the presence or absence of the velocity component for each pixel in the partial image based on the magnitude of the degree, and a plurality of partial images overlapping each other. Means for determining a speed component for each pixel included in the region where the pixel has a speed component and for a pixel for which a plurality of speed components have been estimated, using the degree having the plurality of speed components.

The recording medium on which the moving image speed field measuring program of the present invention is recorded is a process for dividing a moving image into a plurality of partial images overlapping each other, and a process for estimating a dominant speed component for each partial image. A process of calculating a degree having an estimated speed component for each pixel in the partial image; a process of determining the presence or absence of a speed component for each pixel in the partial image based on the magnitude of the degree; Are overlapped with each other, and for each pixel included in the region where the pixel has a speed component, and for a pixel for which a plurality of speed components are estimated, a speed component is determined using the degree having the plurality of speed components. A moving image speed field measurement program for causing a computer to execute the processing to be performed is recorded.

The present invention divides a moving image into a plurality of partial images overlapping each other, calculates a dominant translation speed component for each partial image, assigns a speed component to pixels in the partial image, For a wrapped pixel, a velocity component is determined using a plurality of velocity components. Therefore, it is possible to measure a speed field in a moving image whose speed changes depending on a position in an image with a small amount of calculation while ensuring robustness against noise and occlusion.

Further, by giving each pixel a degree having the estimated velocity component, it is possible to determine an appropriate velocity component by integrating a plurality of estimated velocity components in an overlapping area. Becomes

Further, since the degree of the estimated speed is calculated for each pixel in the partial image and the presence or absence of the speed component is determined, discontinuous portions of the speed field such as the boundary between the moving target object and the background are determined. Can measure the stored speed field with high accuracy.

[0012]

Next, embodiments of the present invention will be described in detail with reference to the drawings.

Referring to FIG. 1, a moving image speed field measuring apparatus according to an embodiment of the present invention includes an input unit 100 and a processing unit 200.
And an output unit 300.

The processing unit 200 includes an image division and extraction unit 201 for extracting a partial image from a moving image input at the input unit 100, a speed component estimating unit 202 for estimating a speed component for each partial image, and A contribution calculator 203 for calculating the degree (contribution) of each pixel in the partial image having the velocity component, a contribution memory 204 for storing the contribution for each pixel, and a partial image according to the magnitude of the contribution. Speed component allocating unit 205 that allocates a speed component to each of the pixels inside
And a velocity component memory 206 for storing the velocity assigned to each pixel, and a velocity case component 207 for synthesizing a velocity field from the velocity components and contributions given for all the pixels in the image.

The output unit 300 outputs the speed field of the moving image output from the speed generating unit 207 to a display device or a file device.

FIG. 2 is a flowchart showing the flow of the processing in the embodiment of FIG.

A time-series image is input (step 401).
A partial image is extracted from the moving image (step 402), a velocity component in the partial image is estimated (step 403), and a degree (contribution) having the estimated velocity is calculated for each pixel (step 404). The same processing is performed for the partial image at the position of. Further, after the processing is completed for all the partial images covering the entire image area, the velocity components are combined using the contributions to obtain the velocity field of the entire image (step 406). Finally, the velocity field is output (step 406). Step 40
7).

Hereinafter, an operation example of the processing section 200 will be specifically described.

In the image division / extraction unit 201, the input unit 100
Divides the input moving image into partial images overlapping each other, and extracts individual partial images.

For example, as shown in FIG. 3, an image plane in a moving image is divided into M × N windows centered on M × N grid points, and each partial image is extracted. Adjacent windows overlap each other. Here, the partial image at the grid point (m, n) is represented as I _{m, n} (x, y, t).

Next, the speed component estimating unit 202 inputs the partial image divided and extracted by the image dividing and extracting unit 201, and estimates the most dominant speed component in the image.

Here, as an example, a motion trajectory distribution in which a moving contour included in a plurality of frames of a moving image is drawn in space and time is constructed, and a frequency distribution of a tangent plane tangent to the motion trajectory is obtained by voting. A method of estimating a velocity component by voting from a frequency distribution in a direction of an intersection formed by tangent planes will be described.

First, in order to construct a motion trajectory distribution in which a moving contour is drawn in space-time, a difference between frames of a moving image is calculated, and a spatio-temporal difference image D ( A method of constructing a motion trajectory as (x, y, t) can be used. In the example using positive values,

[0024]

(Equation 1) , A spatiotemporal difference image D (x, t, t) can be calculated, and a columnar motion trajectory having an edge or contour in the image as a bottom curve can be extracted. The magnitude of the gray value of the spatiotemporal difference image D (x, y, t) is substantially proportional to the discontinuity of the spatial distribution of the brightness of edges and contours in the image and the amount of motion. It should be noted that a method of extracting a motion trajectory other than those described above can also be used.

Next, the frequency distribution of a tangent plane that is in contact with the motion trajectory constructed as the time-series difference image D is obtained by voting. Here, a method of obtaining a frequency distribution of a tangent plane in a three-dimensional array using a three-dimensional Hough transform will be described.

Here, as shown in FIG. 4, a plane passing through a point (x _i , y _i , t _i ) in a three-dimensional space is determined by using three parameters (θ, φ, ρ).

[0027]

(Equation 2) Can be expressed as Here, (θ, φ) represents the normal direction of the plane, and ρ represents the shortest distance from the origin to the plane. Three parameters representing the plane (θ, φ, ρ) is be referred in the space here the plane parameter space S _P spanned. From equation (2), one point (x _i , y _i , t) in the three-dimensional space
_i) corresponds to a curved surface in a plane parameter space, such as S ₁ in FIG.

In a three-dimensional Hough transform, the plane parameter space S _P, small gap (△ θ, △ φ, △ ρ) is discretized, which is stored in 3-dimensional array. Here, the elements of the array are called cells.

Next, using the voting, the distribution of the tangent plane of the motion trajectory in the target area represented as the spatiotemporal difference image D is obtained as the value of the cell in the parameter space. Specifically, space-time difference image D (i, j, t) for all the pixels in, computes a curved surface represented by the formula (2), the cells in the parameter space S _P that the curved surface passes The value is increased by the value of the pixel D (i, j, t) in the spatiotemporal difference image. This process is called voting. After voting for all pixels, the total value of the voting of the cells in the plane parameter space _SP (θ, φ, ρ) is defined as the intensity of the tangent plane of the motion trajectory having the parameters (θ, φ, ρ). Therefore, if the distribution of the vote value in the parameter space S _P forms a peak, the coordinates of the peak, tangent plane of movement trajectories included in the time-space can be represented. Note that methods other than those described above can also be used.

Next, a velocity component is estimated by voting from the frequency distribution in the direction of the intersection line formed by the tangent planes.

Before that, the plane parameter space S _P (θ,
For each (θ, φ) in (φ, ρ), the maximum value of the voting values accumulated in the cell is searched in the ρ direction, and the maximum value of the voting is searched for in the two-dimensional normal parameter space that is a two-dimensional array. To be stored. The space formed by (θ, φ) is referred to as a normal parameter space S _N (θ, φ).

[0032]

(Equation 3) This processing has a function of integrating the distribution of the tangent plane of the motion trajectory drawn in the space and time by the contour and the edge in the target area into the distribution when viewed in the normal direction invariant in time and position.

Then, the normal parameter space S _N (θ,
From phi), into a parameter space that represents the direction of the distribution of the intersection line formed by a plurality of tangent planes may contact with the moving path (this is referred to as intersection line parameter space S _L).

Here, the direction of the intersection line is defined as an angle α, xy that forms the x-axis when the intersection line passing through the origin is projected on the xy plane.
Using the angle β made with the plane (image plane),

[0035]

(Equation 4) Is expressed as

[0036] Now, the two different points on the line of intersection solved by simultaneous equation (2), by substituting Equation (4) to (6), the normal parameter space S _N and the line of intersection parameter space S _L
The relationship

[0037]

(Equation 5) Can be obtained as follows.

The two tangent planes are represented as two points in the normal parameter space S _N , and when these points are respectively converted into the intersection parameter space S _L , a curve represented by equation (7) is obtained. As the intersection, the direction of the intersection line of the tangent plane is obtained.

Here, for all the elements (θ, φ) (referred to as cells) of S _{N in} the parameter space of the normal, the cells in the intersection parameter space S _L through which the curve of equation (7) passes are denoted by S _N. Vote on the value of (θ, φ). Such By executing the Hough transformation, the velocity component of the object that may be included in the target region representing the velocity component of the object is reflected in the vote distribution in the line of intersection parameter space S _L.

[0040] detecting the peak of the distribution of the vote value stored in the line of intersection parameter space memory S _L, the coordinate value of the peak (α _p, β _p) from the most dominant translational of the target object in the target area Find the velocity component. The direction of this movement is

[0041]

(Equation 6) And the magnitude V of the velocity is

[0042]

(Equation 7) Is obtained. The voting value S _L (α _p , β _p ) indicating the peak is
This can be said to be evidence information indicating the likelihood that a translation velocity component in the velocity V and the direction α _P exists in the target area. The speed thus obtained is hereinafter referred to as the speed component

[0043]

[Outside 1] It is written.

The speed estimation method described above has an advantage that it is possible to obtain a dominant translation speed component in a partial image robustly against noise and occlusion.

Next, the contribution calculator 203 calculates the degree (contribution) of each pixel in the partial image of the velocity component estimated by the velocity component estimator 202 in the partial image. It is stored in the memory 204.

Here, the following method will be described as an example. From the frequency distribution of the tangent plane forming the direction of intersection corresponding to the speed component estimated by the method given as an example of the speed component estimating unit 202 and the tangent plane including each pixel,
The value of the maximum frequency distribution is determined as the degree of contribution to the estimated velocity component.

The spatiotemporal difference image D (x, y, t) plane may pass one pixel in has a distribution such as the curved surface S ₁ in FIG. 5 of the formula (2). On the other hand, the distribution of the tangent plane having the direction of intersection (α _p , β _p ) of the tangent plane corresponding to the speed estimated by the speed component estimation unit 202 is derived from Expression (7).

[0048]

(Equation 8) A set of cells in a plane parameter space S _P THAT is represented by a curve refers. The distribution is expressed by an equation (1) such as S ₂ in FIG.
It forms a column surface with the curve of 0) as the bottom curve.

Therefore, the velocity component in which one pixel in the partial image is estimated

[0050]

[Outside 2] Is that one pixel is in the intersection parameter space memory S
It can be considered as a ratio contributing to the peak voting value in _L , and each pixel D (x, y, t) has a velocity component

[0051]

[Outside 3] The set of cells in the three-dimensional voting space memory that can contribute to
A curve that satisfies both equations (2) and (10) at the same time, that is, a curve where two curved surfaces in FIG.
Is a set of cells indicated by. Here, it is defined and obtained as the maximum value C (x, y, t) in this set of cells. The contribution C (x, y, t) for each pixel is stored in the contribution memory 204.

It is to be noted that a method of calculating the degree of contribution other than those described above can also be used.

Next, the velocity component allocating section 204 assigns the velocity component estimated by the velocity component estimating section 202 to each pixel based on the magnitude of the contribution calculated for each pixel in the partial image by the contribution calculating section 203. assign.

Here, the following method will be described as an example. The voting value of the intersection line parameter space S _L, includes the effects of variations in the noise and speed in the pixel. It is necessary to exclude these influences, specify a pixel in the spatiotemporal difference image D (x, y, t) that is essential only for the contribution of the velocity component, and add the velocity component.

Therefore, the contribution C (x, y, t) of each pixel
Is assigned a threshold value T, and the speed component estimated by the speed component estimating unit 202 is assigned only to pixels having a contribution degree equal to or larger than the threshold value T. Here, the threshold value T is calculated from the lowest value of the voting value in the intersection line parameter space memory to the peak value _SL (α _p , β
Given a ratio ε when _p ) is set to 1.0, the peak of the intersection parameter space is obtained by the contribution of the voting value by the pixels having the contribution C (x, y, t) equal to or larger than the threshold T. the point (α _P, β _P) voting value is integrated in the _{εS L (α P, β P} )
Set the value of T such that ε is called a contribution rate, and when the input image contains much additional noise, 1.
Give a value close to 0. If the contribution C (x, y, t) is less than the threshold value T, it is determined that the pixel (x, y, t) has no speed. Therefore, the velocity component of each pixel in the spatiotemporal difference image D

[0056]

[Outside 4] Is

[0057]

(Equation 9) And can be assigned. In this way, the velocity component assigned to each pixel in the partial image is stored in the velocity component memory 206.

Finally, in the speed component synthesizing unit 207, for a plurality of partial images extracted by the image division extracting unit 201, the speed component of each pixel in the partial image stored in the speed component memory 206 and the contribution degree Using the degree having the velocity component stored in the memory 204, the velocity field of the entire moving image is obtained.

The following example is shown as one of the methods. Now, for a pixel (x, y) in the entire image, a set of velocity components stored in the velocity component memory 206 is

[0060]

(Equation 10) It expresses. Further, a set of contributions of the pixel (x, y) stored in the contribution memory 204 is

[0061]

[Equation 11] It expresses. Here, q (x, y) is the number of partial images in which the pixels (x, y) overlap, and for pixels in an area where the partial images do not overlap, q
(X, y) = 1, and the final velocity component in the velocity field is

[0062]

[Outside 5] Becomes For pixels in the overlapping area, q (x, y)> 1, and the velocity component in the final velocity field is determined from the plurality of velocity components and their contributions.

[0063]

[Outside 6] To determine.

As one of the methods, a method of determining the speed component as a linear combination of the speed components with the contribution as a weight can be used. Therefore, the contribution degree is set to 0 for a pixel determined to have no speed component by the speed component assignment unit 205. Velocity component in the velocity field where partial images overlap

[0065]

[Outside 7] Is

[0066]

(Equation 12) It can be calculated as follows.

As another method, the velocity component corresponding to the maximum contribution among the plurality of contributions of the overlapping pixel is calculated as the velocity component of the pixel.

[0068]

[Outside 8] The method of determining as is also available.

Further, the velocity component of the pixel in the partial image is
The further away from the center of the partial image, the less reliable it is. Therefore, a method can be used in which the above-mentioned contribution is weighted according to the distance from the center of the partial image.

Note that methods other than those described above can be used.

Referring to FIG. 6, a moving image speed field measuring apparatus according to another embodiment of the present invention includes an input device 501 for inputting a moving image, a contribution memory 204 and a speed component memory 206 shown in FIG. The same contribution memory 502, speed component memory 503, output device 504 such as a display device or a file device for outputting a speed field of a moving image, and FIG.
Input unit 100, image division extraction unit 201,
Speed component estimating unit 202, contribution calculating unit 203, speed component allocating unit 205, speed component synthesizing unit 207, output unit 30
0, a recording medium 505 such as an FD, a CD-ROM, a semiconductor memory, etc., on which a moving image speed field calculation program composed of each process is recorded, and a data processing device 506 for reading and executing the moving image speed field calculation program from the recording medium 505. It is composed of

[0072]

As described above, according to the present invention, when measuring the velocity field in a moving image, the moving image is divided into a plurality of overlapping partial images, and each partial image is predominant. Estimate the velocity component, and calculate the degree having the estimated velocity component for each pixel in the partial image, assign the velocity component according to the magnitude of the degree, and further, a plurality of partial images overlap each other. For each pixel included in the region, and for a pixel for which a plurality of speed components are estimated, by using the degree having the plurality of speed components, the speed component is determined, with a small calculation cost, at high speed, and It is possible to calculate a velocity field of a moving image robustly against noise and occlusion.

[Brief description of the drawings]

FIG. 1 is a configuration diagram of a moving image speed field measuring apparatus according to an embodiment of the present invention.

FIG. 2 is a flowchart of a process of the embodiment of FIG. 1;

FIG. 3 is a diagram showing a state of division into partial images in an image.

FIG. 4 is a diagram illustrating a polar coordinate expression of a plane in a three-dimensional space.

FIG. 5 is a diagram illustrating a state of a tangent plane distribution in a plane parameter space.

FIG. 6 is a configuration diagram of a moving image speed field measuring apparatus according to another embodiment of the present invention.

[Explanation of symbols]

 REFERENCE SIGNS LIST 100 input unit 200 processing unit 201 image division extraction unit 202 speed component estimation unit 203 contribution calculation unit 204 contribution memory 205 speed component assignment unit 206 speed component memory 207 speed component synthesis unit 300 output unit 401 to 407 step 501 input device 502 Contribution memory 503 Speed component memory 504 Output device 505 Recording medium 506 Data processing device

Claims (15)

[Claims] 1. A moving image speed field measuring method for inputting a moving image and measuring a speed field of the moving image, comprising: dividing a moving image into a plurality of partial images overlapping each other; Estimating the dominant velocity component, calculating the degree of the estimated velocity component for each pixel in the partial image, and determining the presence or absence of the velocity component for each pixel in the partial image based on the magnitude of the degree And the degree to which each of the pixels included in the region where the plurality of partial images overlap each other and the pixels have the speed component, and for which the plurality of speed components are estimated, have the respective speed components. Determining a velocity component using the moving image speed field. 2. A step of estimating a dominant velocity component for a divided partial image, constructing a motion trajectory distribution in which a moving contour included in a plurality of frames of the moving image is drawn in space and time, and Find the frequency distribution of the plane,
The moving image speed field measurement method according to claim 1, wherein a speed component is estimated by voting from a frequency distribution in a direction of an intersection formed by the different tangent planes. 3. The degree having the velocity component estimated in claim 2 with respect to each pixel in the partial image is determined by a tangent plane passing through each pixel and a tangent plane forming an intersection line direction corresponding to the velocity component. The moving image speed field measuring method according to claim 2, wherein the moving image speed field measuring method is obtained as a maximum value of a frequency distribution. 4. A method of determining a speed component of a pixel included in an area where a plurality of partial images overlap each other, wherein the linearity of the plurality of speed components weighted by the degree having the plurality of estimated speed components is used. The moving image speed field measurement method according to claim 1, wherein a speed component of a pixel is determined as a combination. 5. The step of determining a velocity component of a pixel included in an area where a plurality of partial images overlap each other corresponds to the largest degree among the degrees having the estimated plurality of velocity components. The moving image speed field measuring method according to claim 1, wherein the speed component is a speed component of the pixel. 6. A moving image speed field measuring apparatus for inputting a moving image and measuring a speed field thereof, comprising: means for dividing the moving image into a plurality of partial images overlapping each other; Means for estimating the dominant velocity component, means for calculating the degree of the estimated velocity component for each pixel in the partial image, and judging the presence or absence of the velocity component for each pixel in the partial image based on the magnitude of the degree A plurality of partial images overlap each other, and the degree of each pixel included in the region where the pixel has a speed component, and the pixel for which the plurality of speed components are estimated has the respective speed components. And a means for determining a velocity component using the moving image velocity field measurement apparatus. 7. A means for estimating a dominant velocity component for a divided partial image, comprising: constructing a motion trajectory distribution in which a moving contour included in a plurality of frames of a moving image is drawn in space and time; 7. The moving image speed field measuring device according to claim 6, wherein the moving image speed field measuring device is means for obtaining a frequency distribution of a plane, and estimating a speed component from the frequency distribution in a direction of an intersection formed by different tangent planes by voting. 8. The degree having the velocity component estimated in claim 7 for each pixel in the partial image is determined by using a tangent plane passing through each pixel and a tangent plane forming an intersection line direction corresponding to the velocity component. The moving image speed field measuring device according to claim 7, wherein the moving image speed field measuring device is means for obtaining the maximum value of the frequency distribution. 9. A method for determining a velocity component of a pixel included in an area where a plurality of partial images overlap each other, the method comprising: determining a linearity of a plurality of velocity components by weighting the degree having the estimated plurality of velocity components. The moving image speed field measurement apparatus according to claim 6, wherein the combination is means for determining a speed component of a pixel. 10. A means for determining a velocity component of a pixel included in a region where a plurality of partial images overlap each other corresponds to a largest value among the degrees having the estimated plurality of velocity components. 9. The moving image speed field measuring apparatus according to claim 6, wherein the speed component is means for setting a speed component of the pixel. 11. A recording medium on which a moving image is input and a moving image speed field measuring program for measuring a speed field is recorded, wherein the processing is performed to divide the moving image into a plurality of partial images overlapping each other. A process of estimating a dominant speed component for each partial image, a process of calculating a degree having an estimated speed component for each pixel in the partial image, and a speed for each pixel in the partial image according to the magnitude of the degree. With the process of determining the presence or absence of a component, a plurality of partial images overlap, each pixel included in the region where the pixel has a speed component, and for a pixel for which a plurality of speed components are estimated,
A recording medium storing a moving image speed field measurement program to be executed by a computer having a process of determining a speed component using the degree having each speed component. 12. A process for estimating a dominant velocity component for a divided partial image comprises constructing a motion trajectory distribution in which a moving contour included in a plurality of frames of a moving image is drawn in space and time, and 12. The recording medium according to claim 11, wherein the process is a process of obtaining a frequency distribution of a plane, and estimating a velocity component by voting from a frequency distribution in a direction of an intersection formed by different tangent planes. 13. The method according to claim 1, wherein each pixel in the partial image is provided.
13. The processing according to claim 12, further comprising the step of obtaining the degree having the velocity component estimated in 2 as a maximum value of the frequency distribution of a tangent plane passing through each pixel and forming a direction of intersection corresponding to the velocity component. The recording medium according to the above. 14. A process for determining a velocity component of a pixel included in an area where a plurality of partial images overlap each other is performed by performing linear processing on a plurality of velocity components weighted by a degree having the estimated plurality of velocity components. 14. The method according to claim 11, wherein the combination is processing for determining a velocity component of a pixel.
The recording medium according to Item. 15. A process for determining a velocity component of a pixel included in an area where a plurality of partial images overlap each other corresponds to the largest value among the estimated degrees having a plurality of velocity components. The recording medium according to any one of claims 11 to 13, wherein the processing is a process in which a speed component is set as a speed component of the pixel.