KR102289695B1 - Motion Data Recording Method of Human Animation by Singular Point Extraction - Google Patents

Abstract

The present invention relates to a motion data recording method of a human animation through singular point extraction to optimize motion data applied to a human animation (human three-dimensional model) when creating animation content through a three-dimensional engine such as Unity or Unreal. According to the present invention, the motion data recording method of a human animation records motion data of a human animation through a motion data recording apparatus and comprises: a step of collecting motion data for creating a human animation by a data collection unit (120) of the motion data recording apparatus (100); a step of designating a singular point extraction point (n) of a three-dimensional animation human model by a singular point extraction unit (130), and assigning a weight (w^n) for each designated point; and a step of extracting a singular point of collected motion data in accordance with the weight (w^n) assigned for each point and a singularity degree by the singular point extraction unit (130), and recording motion data after compressing the motion data by selecting a frame stored based on a singular point extracted through the singular point extraction unit (130) by a compression performing unit (140). The capacity of motion data can be effectively compressed and recorded.

Description

{Motion Data Recording Method of Human Animation by Singular Point Extraction}

The present invention relates to a method for recording motion data of human animation, and in particular, when animation content is produced through a 3D engine such as Unity or Unreal, motion through singular point extraction for optimization of motion data applied to human animation (human 3D model) How to record data.

Motion capture refers to the work of attaching a sensor to the body or using an infrared camera, etc. to capture the movement of the human body and record it in digital form. Motion data obtained through such motion capture is digital content and is used in various ways, such as animation, movie games, motion analysis, and rehabilitation.

As one of these motion capture methods, there is a method of attaching a motion sensor to a 3D human model and recording the motion data of the human animation by detecting the motion of the motion sensor. However, when creating animations using 3D human models, the rotation direction (Euler or quaternion) and position of all joints and nodes of the 3D human model must be saved for each frame, so it is necessary to create and apply an excessively large file. there was a problem with In particular, there was a problem in that the production period and efficiency were reduced due to the rapid increase in rendering time as well as excessive increase in capacity when producing animations expressing the motion of multiple models or crowds of two or more people.

Republic of Korea Patent Publication No. 10-1519775 (Registered on May 6, 2015) Republic of Korea Patent Publication No. 10-0415884 (Registered on Aug. 1, 2004)

The present invention has been proposed to solve a problem that occurs when recording motion data of a conventional human animation, and an object of the present invention is to accurately record a motion by compressing and recording the capacity of motion data applied to a human animation through extraction of a singularity of the motion. An object of the present invention is to provide a method of recording motion data of a human animation that can reduce the amount of motion data while expressing it.

A method for recording motion data of a human animation according to the present invention for achieving the above object is a method of recording motion data of a human animation through a motion data recording device. collecting motion data; Designating the singularity extraction point (n) of the 3D animation human model in the singularity extraction unit, and assigning a weight (w ⁿ ) to each designated point; The singularity extractor extracts the singularity of the motion data collected according to the weight (w ⁿ ) given to each point and the degree of singularity, and the compression performing unit selects a frame to be stored based on the singularity extracted through the singularity extractor. and recording the motion data after compression.

In the step of assigning a weight for each point, a region where a motion occurs in the human model is designated as an extraction point (n), and a weight (w ⁿ ) for each designated extraction point is equally or differentially applied.

)를 구하는 단계와, 구해진 각 프레임의 예측 변위(

)와 실제 변위(

), 예측 변위를 추정한 이전 프레임의 변위(

) 정보를 이용하여 특이정도를 계산하는 단계와, 계산된 특이정도와 포인트 별 가중치를 이용하여 특이점을 추출하고 추출된 특이점을 바탕으로 모션 데이터를 압축하여 레코딩하는 단계를 포함한다. In addition, in the step of recording after compression of the motion data, the singular point extraction of the motion data _{includes the steps of storing the initial displacement (P 0} ⁿ ) of each extraction point of the original motion data, and the displacement of each extraction point for each frame of motion data rate of change vectors (V _t ⁿ⁾ of each frame predicting the displacement of the motion data by using the phase and the extracted vector displacement change rate (V _t ⁿ⁾ for extracting (

), and the predicted displacement (

) and the actual displacement (

), the displacement of the previous frame from which the predicted displacement was estimated (

) calculating the singularity using the information, extracting the singularity using the calculated singularity and weight for each point, and compressing and recording motion data based on the extracted singularity.

)와 예측 변위(

)를 통하여 계산된 특이정도의 방향(

)이 특이점 추출 방향 기준값인

보다 클 경우 특이점으로 판단하여 실제 변위(

)를 저장하고, 특이정도의 방향(

)이 특이점 추출 방향 기준값인

보다 작은 경우, 계산된 특이정도 크기(

)가 특이점 추출 크기 기준값인 T보다 클 경우 특이점으로 판단하여 가중치 적용을 진행하며, 한 프레임에서 모든 포인트의 특이정도 크기(

) 계산 후, 특이점 추출 크기 기준값과 비교하여 한 포인트라도 기준값(T)을 초과 할 경우 그 차이와 가중치를 곱한 값의 제곱근으로 특이점 추출 게인값(D ; gain value)을 계산하고, 계산된 게인값(D)이 특이점 추출 판단값(D^T)보다 클 경우 최종 특이점 추출로 판단하여 현재 프레임을 저장하여, 특이점으로 판단된 프레임 저장을 통해 최종 모션 데이터 압축이 수행되게 된다. The step of extracting the singularity and compressing and recording motion data based on the extracted singularity includes the actual displacement (

) and the predicted displacement (

), the direction of the specificity calculated through (

) is the reference value for the outlier extraction direction.

If it is larger than the actual displacement (

), and the direction of the singularity (

) is the reference value for the outlier extraction direction.

If less than, the calculated singularity size (

) is larger than the standard value of the size of the singularity extraction, T, it is determined as a singularity and weight is applied, and the singularity size (

) after calculation, if even one point exceeds the reference value (T) compared with the reference value of the size of the singularity extraction, the gain value (D ; gain value) is calculated as the square root of the value multiplied by the difference and the weight, and the calculated gain value If (D) is greater than the singularity extraction determination value (D ^T ), the final singularity extraction is determined and the current frame is stored, and the final motion data compression is performed through the storage of the frame determined as the singularity point.

Meanwhile, in the step of collecting the motion data, the data collection unit re-records the motion data generated through the motion capture system expressing the motion of the human body, the motion data generated by the animator directly manipulating the joint key of the character, and data optimization. Any one of the existing recorded motion data for this purpose is collected.

According to the motion data recording method of the human animation of the present invention, it is possible to accurately express the motion that the animator wants to express by extracting the singularity of the motion, away from the conventional method of simply deleting and compressing frames at regular intervals, and the capacity of the motion data It has the effect of effectively compressing and recording. In particular, the present invention provides not only the motion data of the motion capture system that expresses the motion of the human body as it is, but also the motion data collected by the animator by directly manipulating the character's joint key, the existing motion data for re-recording for data optimization (compression). It has the effect of enabling effective recording for various motion data such as

In addition, the present invention has the effect of reducing the amount of motion data that rapidly increases when expressing the motion of a crowd, thereby shortening the production period by reducing the rendering time and increasing the efficiency of the work.

1 is a block diagram of an apparatus for recording motion data of human animation according to the present invention;
2 is a flowchart showing a motion data recording process through the motion data recording apparatus of human animation according to the present invention;
3 is a conceptual diagram of a singular point extraction point and weighting of a 3D animation human model applied to the present invention;
4 is a conceptual diagram of extracting a vector between each displacement for each frame of motion data according to the present invention;
5 is a conceptual diagram for predicting a displacement position of each frame of motion data according to the present invention;
6 is a conceptual diagram illustrating a process of calculating the magnitude of the singularity with respect to the displacement position of each frame of motion data according to the present invention;
7 is a conceptual diagram of extracting a singular point for a displacement position of each frame of motion data according to the present invention;
8 is a conceptual diagram illustrating a process of comparing the magnitude of the degree of singularity calculated for the displacement position of each frame of motion data and the reference value for extracting the singularity according to the present invention;
9 is a conceptual diagram illustrating a condition for determining the direction of the singularity with respect to the displacement position of each frame of motion data according to the present invention;
10 is a conceptual diagram illustrating a method of calculating a direction of singular information for a displacement position of each frame of motion data according to the present invention;
11 is a flowchart showing a process in which the final singularity of motion data is extracted and compression is performed according to the present invention;
12 shows an example of final compressed data of motion data according to the present invention.

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

1 is a block diagram of an apparatus for recording motion data of human animation according to an embodiment of the present invention.

As shown in FIG. 1, the apparatus 100 for recording motion data for human animation according to the present invention effectively compresses and records motion data through singular point extraction of motion data applied to human animation. The data recording apparatus 100 may be manufactured with a 3D engine for animation content production, which is a program mounted and driven in a computer.

In the motion data recording apparatus 100 for human animation according to the present invention, a motion data collecting unit 120 for collecting motion data from the outside, a singularity extracting unit 130 for extracting a singularity of the collected motion data, and the A compression performing unit 140 for performing recording by performing compression of motion data based on the singularity extracted through the singularity extraction unit 130, and a control unit 110 for controlling the operation of each component are provided.

The motion data collection unit 120 collects motion data applied to the human animation model, and the motion data collection unit 120 includes not only motion data generated through a motion capture system expressing human motion as it is, but also animators. The motion data generated by directly manipulating the character's joint key and the existing recorded motion data are collected for re-recording for data optimization (compression).

The singularity extractor 130 extracts a singularity for optimization of the motion data collected through the motion data collection unit 120, and the singularity extractor 130 designates a singularity extraction point from the collected motion data. A weight is given to each designated point, an initial displacement is set for each point, a vector between each displacement is extracted, and a displacement position for each frame is predicted. In addition, the degree of singularity (magnitude and direction) is calculated using the predicted displacement and actual displacement information, and the final singularity is extracted using the calculated singularity and weight for each point.

The compression performing unit 140 performs compression of the motion data based on the singularity extracted through the singularity extraction unit 130 to record the motion data.

Hereinafter, a process of recording motion data through the motion data recording apparatus 100 of a human animation configured as described above will be described.

2 is a flowchart illustrating a motion data recording process through an apparatus for recording motion data of a human animation according to an embodiment of the present invention.

Step S100: First, the motion data collection unit 120 of the motion data recording apparatus 100 of human animation collects motion data, and the motion data collection unit 120 uses a 3D human model when producing animation content. Motion data can be collected through the following three methods.

1) Motion capture system

2) Animator manipulation data: An animator directly creates motion data by rotating and moving the joints and nodes of the 3D model.

3) Existing recording data

In the motion data collected through the motion data collection unit 120, the positions of the beginning and the end of all joints and nodes of the 3D model are stored for each frame.

Step S110: When motion data is collected through the motion data collecting unit 120, the singularity extraction unit 130 first designates a singularity extraction point for extracting the singularity of the motion data. In the present invention, instead of considering all points of the human model when extracting the singularity, the point for extracting the singularity of the human model is generally based on the place where the change in displacement is greatest when expressing motion. If you want to emphasize detailed movement, the animator can add extraction points, and it is also possible to reduce the points to reduce capacity.

Step S120: In addition, the singularity extraction unit 130 assigns a weight to each point after designating the points. This weight may be equally applied to all points, or a high weight is applied to the position point that the animator wants to emphasize when expressing motion. It is also possible to give This weight for each point is finally used to determine whether to extract the singularity by comparing it with the reference singularity along with the singularity when motion data is compressed.

은 시간(또는 프레임) t에서의 n번째 포인트에서 발생하는 변위 정보를.

은 n번째 포인트의 가중치를 나타낸다. 3 shows a conceptual diagram of a singular point extraction point and weighting of a 3D animation human model applied to the present invention. As shown in FIG. 3, in the embodiment of the present invention, each singular point extraction point (n; 1 to 7) is designated in a part with a lot of movement in the human model (both ankles, both wrists, both elbows, and the crown of the head), A weight (w ⁿ ) was given to each point. 3, n is the singularity extraction point, t is the time (frame time),

is the displacement information occurring at the nth point in time (or frame) t.

denotes the weight of the nth point.

Step S130: Also, the singular point extractor 130 stores the initial displacement of each point. Since a displacement vector cannot be obtained for each point of the initial motion data, the point displacement of the initial motion data is stored as an initial value. Accordingly, when n points are designated in FIG. 3 , the weight and initial displacement of each point are expressed as follows.

: 애니메이터가 지정한 n번째 포인트의 가중치

: Weight of the nth point specified by the animator

: n번째 포인트의 최초 변위

: the initial displacement of the nth point

를 다음의 수학식 1와 같이 구할 수 있다. Step S140: When the initial displacement for each point is stored, the singular point extractor 130 extracts a vector between the displacements of the points for each frame of the motion data. 4 shows a method of extracting a vector between each displacement. When the n-th point of the first motion data moves from P ₀ to P ₁ , P ₂ , P ₃ , the displacement of the n-th point for each frame rate of change vector

can be obtained as in Equation 1 below.

(where t is the time of the frame, t _t is the current time, and t _(t-1) is the previous frame time)

를 이용하여 각 프레임의 예측 변위

을 다음의 수학식 2와 같이 예측하게 된다. Step S150: When the vector between each displacement is extracted through the above process, the singular point extractor 130 predicts the displacement position of each frame by using the vector between the displacements. 5 is a diagram illustrating a process of predicting the displacement position of each frame, and is a vector rate of change of displacement based on the ^nth _{point P t n .}

Predicted displacement of each frame using

is predicted as in Equation 2 below.

(where t is the frame time, t _t is the current time, and t _t+1 is the next frame time to predict the displacement)

(수학식 2에서 계산된 예측 변위

의 시간 t+1은 다음 프레임에서 현재 시간 t가 되므로, 이하에서는 예측 변위를 현재 시간인

로 기재한다)과 모션 데이터의 실제 변위

, 그리고

를 추정한 이전 프레임의 변위

을 이용하여 모션 데이터의 특이정도를 계산한다. Step S160: Thereafter, the singularity extraction unit 130 calculates the degree of singularity of the motion data, and the calculated singularity information is used to extract the singularity. Predicted displacement obtained in the above process in an embodiment of the present invention

(The predicted displacement calculated in Equation 2

Since the time t+1 of becomes the current time t in the next frame, the predicted displacement is

) and the actual displacement of the motion data.

, And

Displacement of the previous frame estimated by

is used to calculate the specificity of the motion data.

The degree of singularity calculated in this way serves as a criterion for determining the extraction of the singularity. In the present invention, two methods are used to determine the singularity, namely the magnitude and direction of the singularity.

과 움직임 데이터의 실제 변위

과의 물리적 거리, 즉 스칼라값으로 계산된다. 특이정도

은 다음의 수학식 3과 같이 구해지며, 이를 이용하여 특이정도의 크기

는 수학식 4와 같이 구해진다.1) First, the method of calculating the magnitude of the singularity level for judging the singularity will be described. 6 shows a process of calculating the magnitude of the singularity, and FIG. 7 shows a conceptual diagram of extracting a singularity. As shown in Figs. 6 and 7, the magnitude of the specificity is the predicted displacement.

and actual displacement of motion data

It is calculated as a physical distance from and, that is, a scalar value. special degree

is obtained as in the following Equation 3, and using this, the size of the singularity

is obtained as in Equation (4).

은 예상 변위와 실제 변위와의 차이를 나타낸다)(From here,

represents the difference between the expected displacement and the actual displacement)

가 특이점 추출의 크기 기준값 T보다 작은 값일 경우 예상할 수 있는 범위의 값이므로 실제범위

는 기록되고, 이전 변위

가 속한 프레임은 삭제된다. 즉, 최초 변위

에서 최종 변위

까지 예측할 수 있는 속도와 크기로 변위가 이동한다고 판단할 수 있으므로, 최초 변위와 최종변위만 저장하여 데이터를 압축할 수 있다. 만약,

가 기준치 T보다 클 경우 이전 변위

은 최종 변위임으로

가 속한 프레임은 삭제하지 않고 기록된다. 이와 같이 최종 변위를 반드시 저장함으로써, 모션 애니메이션은 애니메이터가 표현하고자 하는 지점까지 정확하게 표현될 수 있다. 여기에서, 특이점 추출 크기 기준값 T는 압축 정도에 따라 애니메이터가 조절할 수 있도록 하여 압축 정도를 결정할 수 있게 된다. When the specificity magnitude is calculated through the above process, the calculated specificity magnitude is compared with a preset singularity extraction reference value. As shown in Fig. 8, the size of the specificity

If is a value smaller than the size reference value T of the singularity extraction, it is a value within the expected range, so the actual range

is recorded, and the previous displacement

The frame to which it belongs is deleted. That is, the first displacement

final displacement at

Since it can be determined that the displacement moves at a speed and magnitude that can be predicted up to , it is possible to compress the data by storing only the initial displacement and the final displacement. what if,

If is greater than the reference value T, the previous displacement

is the final displacement.

The frame to which belongs is recorded without deletion. By always storing the final displacement in this way, the motion animation can be accurately expressed up to the point the animator wants to express. Here, the singularity extraction size reference value T can be adjusted by the animator according to the degree of compression to determine the degree of compression.

2) Next, a method of calculating the direction of the singularity for the second singularity determination will be described. Since the predicted displacement was predicted while maintaining the directionality of the previous displacement, if the direction of the actual displacement is changed, singularity extraction cannot be performed only with the magnitude of the singularity.

를 기준으로 예측 범위

의 방향이 실제 변위

의 방향에서 결정한 특이점 추출의 방향 기준값 이내에 존재할 때 특이점으로 추출한다. In the present invention, the direction of specificity is the displacement of the previous frame.

Prediction range based on

the direction of the actual displacement

It is extracted as a singularity when it exists within the direction reference value of the singularity extraction determined in the direction of .

를 원점으로 한 구의 녹색으로 표시한 부위에 포함된 예측값

를 유효값으로 결정한다. 9 shows the conditions for determining the direction of the specificity in an embodiment of the present invention, the displacement of the previous frame

The predicted value included in the green area of the sphere with the origin

is determined as a valid value.

를 기준으로 한 실제 변위

로의 벡터

와 예측 변위

로의 벡터

의 내적을 이용하여 계산한다. 10 shows a method for calculating the direction of singularity information in an embodiment of the present invention. The direction of the singularity is the displacement of the previous frame.

actual displacement with respect to

vector of lo

and predicted displacement

vector of lo

is calculated using the dot product of

와

는 다음의 수학식 5 및 6과 같이 계산할 수 있다.Here, the two vectors

Wow

can be calculated as in Equations 5 and 6 below.

와

를 통해 두 벡터의 내적

를 구할 수 있는데, 이때 계산되는 내적값으로 다음의 수학식 7과 같이 두 벡터 사이의 각을 구하여 특이정도의 방향

를 구할 수 있다. The two vectors obtained in this way

Wow

dot product of two vectors through

The direction of singularity can be obtained by calculating the angle between the two vectors as in Equation 7 as the dot product calculated at this time.

can be obtained

는 특이점 추출의 방향 기준값인

이내에 포함되는지 확인하게 되는데, 기준값에 포함되면 이는 예측 가능한 값이므로 실제범위

는 기록되고, 이전 변위

가 속한 프레임은 삭제된다. 이러한 두 번째 판단을 통해서 첫 번째 판단에서 계산한 특이정도의 크기는 기준값을 만족하나 방향성이 상이한 프레임의 포인트를 압축에서 제외하여 압축과정에서 발생할 수 있는 모션 예측 오차를 줄일 수 있게 된다. The direction of the specificity calculated through the above process

is the direction reference value for singularity extraction.

It is checked whether it is within

is recorded, and the previous displacement

The frame to which it belongs is deleted. Through this second determination, the magnitude of the singularity calculated in the first determination satisfies the reference value, but it is possible to reduce the motion prediction error that may occur in the compression process by excluding the points of the frame with different directions from compression.

Steps S170, S180: The singularity extraction unit 130 extracts the final singularity by using the direction and magnitude of the singularity degree calculated through the above process, and the weight for each singularity extraction point (S170), and based on this, the compression performing unit 140 ) is to perform compression (S180).

11 is a flowchart illustrating a process in which a final singularity is extracted and compression is performed according to an embodiment of the present invention.

와 예측 변위

를 이용하여 특이정도 방향이 계산되면, 특이정도의 방향

가 특이점 추출의 방향 기준값인

보다 클 경우 특이점으로 판단하여 실제 변위

를 저장한다. 1) First, the actual displacement of the first point in one frame

and predicted displacement

If the singularity direction is calculated using

is the direction reference value for singularity extraction.

If it is larger than that, it is judged as a singularity and the actual displacement

save the

가 특이점 추출의 방향 기준값인

보다 작은 경우, 다음 단계로 계산된 특이정도 크기

가 특이점 추출의 크기 기준값인 T보다 클 경우 특이점으로 판단하여 가중치 적용 단계로 넘어간다. 2) If the direction of specificity

is the direction reference value for singularity extraction.

If less than, the magnitude of the singularity computed to the next step

If is larger than T, which is the size reference value of the singularity extraction, it is determined as a singularity and proceeds to the weight application step.

) 계산 후, 특이점 추출 크기 기준값과 비교하여 한 포인트라도 기준값(T)을 초과 할 경우, 다음의 수학식 8과 같이, 그 차이와 가중치를 곱한 값의 제곱근으로 특이점 추출 게인값(gain value) D를 계산한다. 게인값 D가 특이점 추출 판단값 D^T보다 클 경우, 최종 특이점 추출로 판단하여 현재 프레임을 저장한다. 3) Singularity size of all points in one frame (

) after calculation, if even one point exceeds the reference value (T) compared with the reference value of the size of the singularity extraction, as in the following Equation 8, as the square root of the value multiplied by the difference and the weight, the singularity extraction gain value D to calculate When the gain value D is ^{greater than the singularity extraction determination value D T} , it is determined as the final singularity extraction and the current frame is stored.

4) The frame determined as a singularity is saved and the final motion data is compressed and recorded.

FIG. 12 shows an example of the final compressed data. If one point is described as an example, the t-1 th, that is, frame #1, is not stored because a singular point is not detected in frame #2 in FIG. 12 . Since the size of the singularity in frame #3 is greater than the reference value T, frame #2 is determined as a singularity and stored.

As described above, in the present invention, a singularity extraction point and weight are given to the 3D animation human model, the singularity is extracted according to the weight and singularity given for each point, and a frame to be stored is selected based on the singularity, and motion data is compressed. By being recorded later, it is possible to effectively compress and record the motion data.

The present invention is not limited to the above-described embodiments, and various modifications and variations can be made by those of ordinary skill in the art to which the present invention pertains within the scope of equivalents of the technical spirit of the present invention and the claims to be described below. Of course, this can be done.

100: motion data recording device 110: control unit
120: motion data collection unit 130: singularity extraction unit
140: compression performing unit

Claims (11)

Collecting motion data for producing a human animation in the data collection unit 120 of the motion data recording apparatus 100 (a) and; (b) designating the singularity extraction point (n) of the 3D animation human model in the singularity extraction unit 130, and assigning a weight (w ^{n) to each designated point;} The singularity extractor 130 extracts ^{the singularity of the motion data collected according to the weight (w n} ) assigned to each point and the degree of singularity, and the compression performing unit 140 extracts the singularity through the singularity extractor 130 . A method of recording motion data of human animation comprising a step (c) of selecting a frame to be stored based on a singularity and recording the motion data after compression,
In the step (c) of being recorded after the motion data is compressed,
Singularity extraction of the motion data is
(c-1) storing _{the initial displacement (P 0} ⁿ ) of each extraction point of the initial motion data;
(c-2) extracting a displacement change rate vector (V _t ⁿ ) of each extraction point for each frame of motion data;
(c-3) Using the extracted displacement change rate vector (V _t ⁿ ), the predicted displacement (

), and
(c-4) The predicted displacement of each frame obtained (

) and the actual displacement (

), the displacement of the previous frame from which the predicted displacement was estimated (

) calculating the specificity using the information;
(c-5) A method for recording motion data for human animation, comprising extracting a singularity using the calculated singularity and weight for each point, and compressing and recording the motion data based on the extracted singularity.
The method of claim 1,
The step (b) of assigning a weight for each point is,
A method of recording motion data for human animation, characterized in that a region where motion occurs in the human model is designated as an extraction point (n), and a weight (w ^{n ) for each designated extraction point is equally or differentially assigned.}
delete The method of claim 1,
In the step (b-2) of extracting the displacement change rate vector (V _t ^{n ),}
When the nth point of the first motion data moves from P ₀ to P ₁ , P ₂ , P _{3 , the rate of change vector V t} ⁿ of the displacement of the nth point for each frame is obtained through the following equation A method of recording motion data for human animation.

(where n is the singular point extraction point, t is the frame time, and P _t ⁿ is the displacement of the nth point)
The method of claim 1,
In the step (c-3) of obtaining the predicted displacement of each frame,
Predicted displacement of each frame

A method for recording motion data of human animation, characterized in that it is obtained through the following equation using the _{rate of change vector V t} ⁿ of the displacement based on the _{displacement P t} ⁿ of the n-th point.

The method of claim 1,
In the step (c-4) of calculating the specificity,
The specificity includes the magnitude and direction of the specificity for extraction of the singularity,
The specificity size (

) is the predicted displacement

and motion data actual displacement of each frame

It is calculated as a scalar value that is the physical distance from
The specificity direction (

) is the displacement of the previous frame

Based on , one actual displacement

vector of lo

and predicted displacement

vector of lo

A method for recording motion data of human animation, characterized in that it is calculated using the dot product of .
7. The method of claim 6,
The specificity size (

) is a motion data recording method of human animation, characterized in that it is calculated through the following equation.

7. The method of claim 6,
The specificity direction (

)silver
vector

with vector

dot product of

Motion data recording method of human animation, characterized in that it is calculated through the following equation using

7. The method of claim 6,
Step (c-5) of extracting the singularity and compressing and recording the motion data based on the extracted singularity,
(i) Actual displacement of the first point of one frame of motion data (

) and the predicted displacement (

), the direction of the specificity calculated through (

) is the reference value for the outlier extraction direction.

If it is larger than the actual displacement (

) and save
(ii) direction of specificity (

) is the reference value for the outlier extraction direction.

If less than, the calculated singularity size (

) is greater than T, which is the standard value of the size of the singularity, it is determined as a singularity and weight is applied.
(iii) Singularity size of all points in one frame (

) after calculation, if even one point exceeds the reference value (T) compared with the reference value for the size of the singularity extraction, the gain value (D ; gain value) is calculated as the square root of the value multiplied by the difference and the weight, and the calculated gain If the value (D) is ^{greater than the singularity extraction judgment value (D T} ), it is determined as the final singularity extraction and the current frame is saved,
(iv) A method for recording motion data of human animation, characterized in that final motion data compression is performed through the storage of frames determined as singularities.
10. The method of claim 9,
The singular point extraction gain value (D) is a motion data recording method of a human animation, characterized in that calculated through the following equation.

The method of claim 1,
In the step (a) of collecting the motion data,
The data collection unit 120 includes motion data generated through a motion capture system expressing the motion of a human body, motion data generated by an animator directly manipulating a character's joint key, and existing recorded motion data for re-recording for data optimization Motion data recording method of human animation, characterized in that any one of the motion data is collected.

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