KR101698133B1 - Customized human body modeling apparatus and method - Google Patents

Customized human body modeling apparatus and method Download PDF

Info

Publication number
KR101698133B1
KR101698133B1 KR1020150084242A KR20150084242A KR101698133B1 KR 101698133 B1 KR101698133 B1 KR 101698133B1 KR 1020150084242 A KR1020150084242 A KR 1020150084242A KR 20150084242 A KR20150084242 A KR 20150084242A KR 101698133 B1 KR101698133 B1 KR 101698133B1
Authority
KR
South Korea
Prior art keywords
model
human body
template model
statistical template
scan data
Prior art date
Application number
KR1020150084242A
Other languages
Korean (ko)
Other versions
KR20160147466A (en
Inventor
김재정
손세민
Original Assignee
한양대학교 산학협력단
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 한양대학교 산학협력단 filed Critical 한양대학교 산학협력단
Priority to KR1020150084242A priority Critical patent/KR101698133B1/en
Publication of KR20160147466A publication Critical patent/KR20160147466A/en
Application granted granted Critical
Publication of KR101698133B1 publication Critical patent/KR101698133B1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T13/00—Animation
    • G06T13/20—3D [Three Dimensional] animation
    • G06T13/40—3D [Three Dimensional] animation of characters, e.g. humans, animals or virtual beings

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Processing Or Creating Images (AREA)

Abstract

A personal body modeling apparatus and method is disclosed. The personalized body modeling apparatus includes a scanning unit that scans a human body and generates scan data for the human body; and a controller that modifies a statistical template model associated with the human body based on the scan data to generate a customized human shape model And a processor for forming the processor.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a customized human body modeling apparatus and method,

Embodiments of the present invention relate to techniques for forming a custom body shape model for a human body based on a statistical template model.

In recent years, the design of a specific person's body shape has been highlighted in various industrial fields such as human body, clothing, game, and automobile. This is the main purpose of improving the convenience and safety by considering the shape of a specific person in the design process of the product, and providing more useful products to the individual.

The conventional human shape generating apparatus can generate a human body shape model of a human body realistically and specifically, but it requires high cost of scanning equipment that supports precise scanning, thus requiring a high cost.

In addition, the human shape generating apparatus can increase the completeness of the noise and the shape surface through a plurality of short-range scans using a low-cost scanning apparatus, but it is considerably cumbersome due to a need to scan a stopped scan object several hundred times, The scan data is inaccurate due to the motion of the scan object, and therefore the quality of the human body shape generated based on the scan data is inevitably lowered.

The present invention relates to a method and apparatus for generating scan data for a human body through a Kinect and modifying a statistical template model associated with the human body based on the scan data to form a customized human shape model for the human body, A statistical template model reflecting the shape of a human body belonging to a population is transformed into a target of scan data and thus a high quality customized human shape model is provided without repeated scans on the human body .

According to the present invention, a size (or a ratio) of a statistical template model associated with a human body is primarily deformed based on joint information extracted from scan data (e.g., joint position and joint length) The object of the present invention is to provide a customized human shape model with a higher quality by deforming the curved surface of the statistical template model so that the curved surfaces of the statistical template model coincide with each other.

According to another aspect of the present invention, there is provided a personal body modeling apparatus for a human body, comprising a scan unit for scanning a human body and generating scan data for the human body, and a controller for modifying a statistical template model associated with the human body based on the scan data, To form a customized human shape model.

The customized human body modeling apparatus may further include a model construction unit that implements the statistical template model using three-dimensional scan data for each human body included in the population to which the human body belongs.

The processor may modify the statistical template model so that the difference between the curved surface of the scan model formed using the scan data and the curved surface of the statistical template model satisfies a set range.

Wherein the statistical template model includes a first function for determining the extent to which the statistical template model is maintained and reflected in the customized human shape model, a second function for curve matching between the scan model and the statistical template model, The statistical template model can be modified by using at least one function among the third function relating to joint matching between models.

Wherein the processor assigns weights to the first function, the second function, and the third function, respectively, so that the curved surface of the scan model and the curved surface of the statistical template model coincide with each other, , And the sum of the three functions, the statistical template model can be modified.

The scan unit may include n (n is a natural number equal to or greater than 3) number of kinect, which are installed at different positions or directions with respect to the human body and generate scan data for each part of the human body.

The processor may combine the scan data generated in each of the n keynets with the information about the n kinks into consideration, and modify the statistical template model using the combined scan data.

According to another aspect of the present invention, there is provided a method of modeling a human body, the method comprising: scanning a human body to generate scan data for the human body; modifying a statistical template model associated with the human body based on the scan data; And forming a customized human shape model.

According to the embodiment of the present invention, scan data for a human body is generated through a key knot, and a statistical template model associated with the human body is modified based on the scan data to form a custom human shape model for the human body Thus, by using a cheap Kinect, a statistical template model reflecting the shape of the human body belonging to the population is transformed by targeting the scan data, so that a high-quality customized human shape model Can be provided.

According to the embodiment of the present invention, the size (or ratio) of the statistical template model associated with the human body is primarily modified based on the joint information extracted from the scan data (for example, the joint position and the joint length) The curved surface of the statistical template model is secondarily deformed so that the curved surface of the model coincides with the curved surface of the statistical template model to provide a customized human shape model of improved quality.

1 is a diagram illustrating a configuration of a custom body modeling apparatus according to an embodiment of the present invention.
2 is a view for explaining an example of a human body modeling process in a customized human body modeling apparatus according to an embodiment of the present invention.
3 is a diagram for explaining an example of a landmark and a statistical template model used in a customized human body modeling apparatus according to an embodiment of the present invention.
FIG. 4 is a view showing an example of joint information extracted from scan data in a customized human body modeling apparatus according to an embodiment of the present invention.
FIG. 5 is a view showing an example of deformation from a scan model and a statistical template model until a customized human shape model is formed by a customized human body modeling apparatus according to an embodiment of the present invention.
FIG. 6 is a view for explaining an example of generating scan data in the customized human body modeling apparatus according to an embodiment of the present invention.
7 is a flowchart illustrating a method of customizing human body modeling according to an embodiment of the present invention.

Hereinafter, an apparatus and method for customizing human body modeling according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram illustrating a configuration of a custom body modeling apparatus according to an embodiment of the present invention.

Referring to FIG. 1, a customized human body modeling apparatus 100 according to an embodiment of the present invention may include a model construction unit 101, a scan unit 103, a processor 105, and a database 107.

The model construction unit 101 generates a sample model using the scan data (for example, three-dimensional whole-body scan data) for each human body included in the population (for example, 20 to 39 year old male or 30 to 49 year old female) And a statistical template model including joint information (for example, the position of joints and the length of joints) can be implemented using each sample model. At this time, the model construction unit 101 may store the statistical template model in the database 107 in association with the population.

The model construction unit 101 can obtain scan data for the human body used in implementing the statistical template model from an external data server (not shown) or a high-performance scanning apparatus (not shown) The scan unit 103 may acquire scan data for the human body.

The model construction unit 101 can generate a statistical template model by matching each sample model on the basis of the landmark specified in each sample model, and through the human segmentation step of dividing the statistical template model into a plurality of regions , And a statistical template model including joint information.

In addition, the model construction unit 101 calculates the statistical objective function (Equation 1)

Figure 112015057485100-pat00001
), The statistical template model can be modified to approach each sample model.

Figure 112015057485100-pat00002

Where E can be a statistical objective function.

Figure 112015057485100-pat00003
Is a data error function that calculates the sum of the squared distances between points so that the curved surface of the statistical template model is as close as possible to the sample model and can be expressed by Equation (2). Also,
Figure 112015057485100-pat00004
The
Figure 112015057485100-pat00005
≪ / RTI >

Figure 112015057485100-pat00006

here,

Figure 112015057485100-pat00007
Of the statistical template model
Figure 112015057485100-pat00008
Third,
Figure 112015057485100-pat00009
A corresponding 4x4 affine transform matrix,
Figure 112015057485100-pat00010
In the target model
Figure 112015057485100-pat00011
A matching point corresponding to < RTI ID = 0.0 &
Figure 112015057485100-pat00012
Is a weight for controlling the influence of the data error function.

Figure 112015057485100-pat00013
Is a function of the deformation error. It is a function of squaring the difference between the transformation of a point on the statistical template model and the transformation of its neighboring points, and can be expressed by Equation (3). Also,
Figure 112015057485100-pat00014
The
Figure 112015057485100-pat00015
≪ / RTI >

Figure 112015057485100-pat00016

Also,

Figure 112015057485100-pat00017
Is a landmark error function that calculates the difference between landmarks between two curved surfaces so that a particular portion of the statistical template model and the corresponding curved surface portion of the sample model are coincident, . Also,
Figure 112015057485100-pat00018
The
Figure 112015057485100-pat00019
≪ / RTI >

Figure 112015057485100-pat00020

here,

Figure 112015057485100-pat00021
Is the number of landmarks,
Figure 112015057485100-pat00022
Of the target model
Figure 112015057485100-pat00023
Th landmark point,
Figure 112015057485100-pat00024
Is an index of a point corresponding to each landmark on the statistical template model.

In addition, the model construction unit 101 can form a scan model using the scan data for the human body generated by the scan unit 103. [

The scan unit 103 may scan a specific human body and generate scan data for the human body. At this time, the scan unit 103 may include, for example, n (where n is a natural number of 3 or more) kinect. Here, the n number of the kinks may be installed at different positions or directions with respect to the human body, and scan data for each part of the human body may be generated.

The processor 105 can form a customized human shape model for the human body by modifying the statistical template model associated with the human body based on the scan data for a specific human body. That is, the processor 105 may reflect the inherent characteristic of a specific human body in the statistical template model associated with the human body, by modifying the statistical template model associated with the human body, using the scan data as a target.

At this time, the processor 105 can identify the population to which the human body belongs, detect the statistical template model corresponding to the identified population from the database 107, and use the statistical template model associated with the human body. For example, when the human body is a human being '25 years old male,' the processor 105 confirms the population of '20 to 39 year old male' as a population to which the human body belongs, A statistical template model corresponding to a population of three males can be detected.

At the time of the transformation, the processor 105 may roughly transform the statistical template model based on the scan data, and finely re-transform it, thereby finely forming the customized human shape model.

Specifically, the processor 105 extracts joint information including at least one of the position of the joint and the length of the joint from the scan data, and based on the extracted joint information, the size of the obtained statistical template model or The ratio (ratio of parts, for example, ratio of arms to legs) can be primarily modified. At this time, when the scan data is generated by the n kinks, the processor 105 converts each scan data into information on the n keynets (e.g., installation position, direction, scan type And the like), and transforms the statistical template model using the combined scan data.

Thereafter, the processor 105 forms a scan model using the scan data through the model construction unit 101, and calculates a difference between the curved surface of the scan model and a statistical template model (for example, a first-order modified statistical template model) The curved surface of the statistical template model (for example, the statistically-modified primary template model) can be secondarily modified so that the difference between the curved surfaces satisfies the set range.

At this time, the processor 105 determines whether or not the statistical template model has a first function (registration error function) for determining the degree to which the statistical template model is maintained and reflected in the customized human shape model, a second function (registration error function) and a third function (connectivity error function) for joint matching between the scan model and the statistical template model may be used to transform the statistical template model. Here, the processor 105 may assign a weight to the first function, the second function, and the third function, respectively, so that the curved surface of the scan model and the curved surface of the statistical template model coincide with each other, The target objective function, which is the sum of the first, second, and third functions (

Figure 112015057485100-pat00025
) Can be used to transform the statistical template model. Here, the target objective function is a curve fitting process for transforming the primarily transformed statistical template model into a scan model, which is a target model, and can be expressed by Equation (5).

Figure 112015057485100-pat00026

Where E can be the target objective function.

Figure 112015057485100-pat00027
Is a registration error function, which means to maintain the shape of the existing statistical template model at the time of transformation, and can be expressed by Equation (6). Also,
Figure 112015057485100-pat00028
The
Figure 112015057485100-pat00029
≪ / RTI >

Figure 112015057485100-pat00030

here,

Figure 112015057485100-pat00031
Of the statistical template model
Figure 112015057485100-pat00032
Third,
Figure 112015057485100-pat00033
The
Figure 112015057485100-pat00034
Th < th > point,
Figure 112015057485100-pat00035
Is a corresponding 4x4 affine transform matrix.

Figure 112015057485100-pat00036
Is a data error function that matches the curved surface of the statistical template model as close as possible to the curved surface of the scan model (target model) and can be expressed by Equation (7). Also,
Figure 112015057485100-pat00037
The
Figure 112015057485100-pat00038
≪ / RTI >

Figure 112015057485100-pat00039

here,

Figure 112015057485100-pat00040
The number of points constituting the model,
Figure 112015057485100-pat00041
Is a weight for adjusting the influence of data error. Also,
Figure 112015057485100-pat00042
Of the template model
Figure 112015057485100-pat00043
Third,
Figure 112015057485100-pat00044
In the scan model (target model)
Figure 112015057485100-pat00045
Lt; / RTI >

Figure 112015057485100-pat00046
Is a connectivity error function that matches the joint positions between the statistical template model and the scan model (target model), and can be expressed by Equation (8). Also,
Figure 112015057485100-pat00047
The
Figure 112015057485100-pat00048
≪ / RTI >

Figure 112015057485100-pat00049

here,

Figure 112015057485100-pat00050
Is the number of joints,
Figure 112015057485100-pat00051
Is the coordinates of the joint point of the statistical template model,
Figure 112015057485100-pat00052
Is the coordinates of the joint point of the scan model (target model).

The database 107 may store a statistical template model corresponding to the population.

The personalized human body modeling apparatus 100 according to an embodiment of the present invention uses a statistical template model reflecting the shape of a human body belonging to a population as an overall basic format and targets the scan data for a specific human body, By modifying the template model step by step, a high-quality customized human shape model can be quickly and easily formed. At this time, by using the statistical template model, the customized human body modeling apparatus 100 can easily supplement the portion where the scan data for the human body does not include a part (for example, an arm or a leg) .

2 is a view for explaining an example of a human body modeling process in a customized human body modeling apparatus according to an embodiment of the present invention. FIG. 3 is a view for explaining an example of landmark and statistical template model implementation, FIG. 4 is an illustration of an example of joint information extracted from scan data, FIG. 5 is a diagram Fig.

Referring to FIG. 2, the customized human body modeling apparatus according to an embodiment of the present invention acquires three-dimensional scan data for each human body included in the population of '20 to 39 year old male' The statistical template model 203 can be implemented based on each sample model 201 generated using the scan data.

Here, the customized human body modeling apparatus is a parameter commonly used for each sample model in order to statistically analyze the human body shape. For example, a landmark (for example, 64 landmarks) can be specified. The landmark specified in the sample model can be utilized in the surface fitting process for statistical template model implementation.

Also, as shown in FIG. 3 (b), the customized human body modeling apparatus can generate a statistical template model by matching the respective sample models based on the landmarks specified in the individual sample models, Is divided into a plurality of regions, and a statistical template model including joint information can be implemented through the human segmentation step.

The customized human body modeling device is a specific human body that scans the human body of a '25 year old male' to generate scan data 205 for the human body, and generates a '20 to 39 year old male' A customized human shape model for the human body of the '25-year-old male' can be formed by using the statistical template model 203 corresponding to the population and the scan data 205 for the human body of the '25 year old male. At this time, on the basis of the scan data 205 for the human body of the '25-year-old male', the customized human body modeling device gradually transforms the statistical template model 203 corresponding to the population of the '20-39 year old male' It is possible to form a custom body shape model for a human body of a '25-year-old male'.

Specifically, the customized human body modeling device extracts joint information including at least one of the position of the joint and the length of the joint from the scan data 205 for the human body of the "25 year old male", and based on the extracted joint information The statistical template model 203 corresponding to the population of the '20 to 39 year old male' can be primarily modified in size or ratio to form the statistical template model 207 of the first-order transformation. At this time, from the scan data 205 for the human body of the "25-year-old male", the customized human body modeling device is the joint information that has the greatest influence on the ratio of the human body. For example, as shown in FIG. 4, The statistical template model 203 corresponding to the population of the '20 to 39 year old male' can be modified by extracting the lengths (1, 2, ..., 10) and using the lengths of the 10 joints as variables .

Thereafter, the customized human body modeling apparatus forms a scan model 209 by using the scan data 205 for the human body of the '25-year-old male', and calculates a curved surface of the scan model 209 and a statistical template model By deforming the curved surface of the statistical template model 207 of the first-order deformation secondarily to generate the second-order statistical template model 211 so that the difference between the curved surfaces of the first and second deformation templates 207 and 207 satisfies the set range, Can be formed.

As a result, as shown in FIG. 5, the customized human body modeling apparatus forms a customized human body shape model for the human body using a scan model and a statistical template model for the human body, And the line (or the surface) of the modified statistical template model is modified secondarily to reflect the characteristics of the scan model so as to form a highly matched customized human shape model .

6 is a view for explaining an example of a human body scan in a customized human body modeling apparatus according to an embodiment of the present invention.

Referring to FIG. 6, the customized human body modeling apparatus can scan a specific human body through the scan unit and generate scan data for the human body. At this time, the customized human body modeling apparatus can scan the human body through three first, second, and third keynotes 601, 603, and 605 as the scan unit.

The first, second, and third keyrings 601, 603, and 605 may be installed at different positions or directions with respect to the human body. For example, the first, second, and third keys may be installed at upper, Or on the front, side, and rear surface of the human body, respectively. At this time, the first, second, and third keys (601, 603, and 605) are configured to individually receive different portions (e.g., an upper portion including a face, a middle portion including a body, Scan, or scan the entire body from different angles.

The customized human body modeling device transmits the generated scan data through the first, second and third keyrings 601, 603 and 605 to the first, second and third keys 601, 603 and 605 (for example, 1, 2, 3 Kinect mounting position, direction, scan type (whole body / part), etc.) can be combined. The customized human body modeling apparatus can form a customized human shape model for the human body by modifying a statistical template model associated with the human body based on the combined scan data.

7 is a flowchart illustrating a method of customizing human body modeling according to an embodiment of the present invention.

Referring to FIG. 7, in step 701, a custom body modeling device may implement a statistical template model. At this time, the customized human body modeling device may implement the statistical template model using three-dimensional scan data for each human body included in the population, and store the statistical template model in the database in association with the population.

In step 703, the customized human body modeling device can scan the human body and generate scan data for the human body. At this time, the customized human body modeling apparatus can generate scan data for each part of the human body through n (n is a natural number equal to or larger than 3) kinks provided at different positions or directions with respect to the human body.

In step 705, the customized human body modeling device can modify the statistical template model associated with the human body based on the scan data for the human body, thereby forming a customized human shape model for the human body. At this time, the customized human body modeling apparatus can identify a population to which the human body belongs, detect a statistical template model corresponding to the identified population from the database, and use the statistical template model associated with the human body.

In the modification of the statistical template model, the customized human body modeling device extracts joint information including at least one of the position of the joint and the length of the joint from the scan data, and based on the extracted joint information, The size or proportion of the model can be modified primarily. At this time, if the customized human body modeling apparatus generates scan data by the n number of keynets, the individual human body modeling apparatus generates each scan data by using information on the n number of keynets (e.g., installation position, direction, And the like), and transforms the statistical template model using the combined scan data.

Thereafter, the customized human body modeling device can secondarily modify the curved surface of the statistical template model so that the difference between the curved surface of the scan model formed using the scan data and the curved surface of the statistical template model satisfies the set range.

In this case, the customized human body modeling apparatus may further include a first function for determining the extent to which the statistical template model is maintained and reflected in the customized human shape model, a second function for curve matching between the scan model and the statistical template model, And a third function relating to joint matching between the statistical template model, may be used to transform the statistical template model. Herein, the customized human body modeling device assigns weight values to the first function, the second function, and the third function so that the curved surface of the scan model and the curved surface of the statistical template model coincide with each other, The statistical template model can be modified using a target objective function that is a sum of the first, second, and third functions.

An embodiment of the present invention is characterized by generating scan data for a human body through a Kinect and modifying a statistical template model associated with the human body based on the scan data to form a customized human shape model for the human body, By reducing the cost of using cheap Kinect and transforming the statistical template model that reflects the shape of the human body belonging to the population as the target of the scan data, it provides a high quality custom body shape model without repetitive scans on the human body can do.

In the embodiment of the present invention, the size (or ratio) of the statistical template model associated with the human body is primarily modified based on the joint information extracted from the scan data (for example, the joint position and the inter-joint length) The curved surface of the statistical template model is secondarily deformed so that the curved surface and the curved surface of the statistical template model coincide with each other, thereby providing a customized humanoid shape model of improved quality.

The method according to an embodiment may be implemented in the form of a program instruction that may be executed through various computer means and stored in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions stored on the medium may be those specially designed and constructed for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable storage media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magneto-optical media such as floppy disks; Includes hardware devices specifically configured to store and execute program instructions such as magneto-optical media and ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

100: Customized body modeling device
101:
103:
105: Processor
107: Database

Claims (15)

A scan unit for scanning the human body and generating scan data for the human body; And
A processor for transforming a statistical template model associated with the human body based on the scan data to form a customized human shape model for the human body,
Lt; / RTI >
The scan unit
And n (n is a natural number equal to or greater than 3) number of kinect, which are provided at different positions or directions with respect to the human body and generate scan data for each part of the human body,
The processor
The statistical template model is used to supplement the portion of the human body not included in the scan data to be included in the scan data,
Modifying the statistical template model so that a difference between a curved surface of a scan model formed using the scan data and a curved surface of the statistical template model satisfies a set range,
The statistical template model
Wherein the template model is detected from a database corresponding to a population to which the human body belongs.
The method according to claim 1,
And a model construction unit for implementing the statistical template model using three-dimensional scan data for each human body included in the population to which the human body belongs,
Further comprising:
The method according to claim 1,
The processor comprising:
Extracting joint information including at least one of the position of the joint and the length of the joint from the scan data and modifying the size or the ratio of the statistical template model based on the extracted joint information
Customized body modeling device.
delete The method according to claim 1,
The processor comprising:
Wherein the statistical template model includes a first function for determining the degree to which the statistical template model is maintained and reflected in the customized human shape model,
A second function relating to the surface matching between the scan model and the statistical template model,
And a third function relating to joint matching between the scan model and the statistical template model to transform the statistical template model
Customized body modeling device.
6. The method of claim 5,
The processor comprising:
The first function, the second function, and the third function so that the curved surface of the scan model and the curved surface of the statistical template model coincide with each other, and the weighted first, second, and third functions Of the statistical template model using the target objective function,
Customized body modeling device.
delete The method according to claim 1,
The processor comprising:
Combining the scan data generated in each of the n keykits in consideration of the information on the n kinks and modifying the statistical template model using the combined scan data
Customized body modeling device.
Scanning the human body to generate scan data for the human body; And
Modifying a statistical template model associated with the human body based on the scan data to form a customized human shape model for the human body
Lt; / RTI >
The step of generating the scan data
Generating scan data for each part of the human body through n (n is a natural number equal to or larger than 3) kinks provided at different positions or directions with respect to the human body,
Wherein the step of forming the customized human-
Supplementing the portion of the human body not included in the scan data to be included in the scan data using the statistical template model; And
Transforming the statistical template model so that a difference between a curved surface of a scan model formed using the scan data and a curved surface of the statistical template model satisfies a set range
Lt; / RTI >
The statistical template model
Wherein the template model is detected from a database corresponding to the population to which the human body belongs.
10. The method of claim 9,
Implementing the statistical template model using three-dimensional scan data for each human body included in the population to which the human body belongs,
Further comprising the steps of:
10. The method of claim 9,
Wherein the step of forming the customized human-
Extracting joint information including at least one of a position of the joint and a length of the joint from the scan data; And
Modifying a size or a ratio of the statistical template model based on the extracted joint information
Wherein the method comprises the steps of:
delete 10. The method of claim 9,
Wherein transforming the statistical template model comprises:
Wherein the statistical template model includes a first function for determining the degree to which the statistical template model is maintained and reflected in the customized human shape model,
A second function relating to the surface matching between the scan model and the statistical template model,
Transforming the statistical template model using at least one function of a third function relating to joint matching between the scan model and the statistical template model
Wherein the method comprises the steps of:
14. The method of claim 13,
Wherein transforming the statistical template model comprises:
Assigning weights to the first function, the second function, and the third function, respectively, so that the curved surface of the scan model and the curved surface of the statistical template model coincide with each other; And
Modifying the statistical template model using a target objective function consisting of the sum of the weighted first, second and third functions
Further comprising the steps of:
10. The method of claim 9,
Wherein the step of forming the customized human-
Combining the scan data generated in each of the n kinks by considering information on the n kinks, and modifying the statistical template model using the combined scan data
Wherein the method comprises the steps of:
KR1020150084242A 2015-06-15 2015-06-15 Customized human body modeling apparatus and method KR101698133B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
KR1020150084242A KR101698133B1 (en) 2015-06-15 2015-06-15 Customized human body modeling apparatus and method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
KR1020150084242A KR101698133B1 (en) 2015-06-15 2015-06-15 Customized human body modeling apparatus and method

Publications (2)

Publication Number Publication Date
KR20160147466A KR20160147466A (en) 2016-12-23
KR101698133B1 true KR101698133B1 (en) 2017-01-19

Family

ID=57736052

Family Applications (1)

Application Number Title Priority Date Filing Date
KR1020150084242A KR101698133B1 (en) 2015-06-15 2015-06-15 Customized human body modeling apparatus and method

Country Status (1)

Country Link
KR (1) KR101698133B1 (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102655987B1 (en) * 2018-11-21 2024-04-11 한국전자통신연구원 Apparatus and method for generating 3d avatar
CN110321090B (en) * 2019-07-12 2024-02-20 广东工业大学 Protective clothing manufacturing device and method
KR102402031B1 (en) 2020-11-27 2022-05-27 임대순 System for manufacturing customized clothing using shape memory material
CN116269455B (en) * 2023-03-20 2023-12-12 瑞石心禾(河北)医疗科技有限公司 Detection method and system for automatically acquiring human body contour in SPECT (single photon emission computed tomography)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101466123B1 (en) * 2014-05-27 2014-11-28 한양대학교 산학협력단 Parametric modeling method of human body shape using statistical analysis

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101466123B1 (en) * 2014-05-27 2014-11-28 한양대학교 산학협력단 Parametric modeling method of human body shape using statistical analysis

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Jing Tong ET AL., Scanning 3D Full Human Bodies using Kinects, IEEE, 2012.03.09., 643-650P*

Also Published As

Publication number Publication date
KR20160147466A (en) 2016-12-23

Similar Documents

Publication Publication Date Title
KR102647351B1 (en) Modeling method and modeling apparatus using 3d point cloud
CN106228162B (en) A kind of quick object identification method of mobile robot based on deep learning
KR101997500B1 (en) Method and apparatus for generating personalized 3d face model
KR101994316B1 (en) Device and method for object pose estimation
US9978119B2 (en) Method for automatic facial impression transformation, recording medium and device for performing the method
KR101698133B1 (en) Customized human body modeling apparatus and method
JP4950787B2 (en) Image processing apparatus and method
CN109598781B (en) Method for acquiring pseudo 3D frame from 2D bounding frame by regression analysis, learning apparatus and testing apparatus using the same
US20080285801A1 (en) Visual Tracking Eye Glasses In Visual Head And Eye Tracking Systems
US10839526B2 (en) Information processing device, information processing method, and recording medium
KR20170000748A (en) Method and apparatus for face recognition
CN104346608A (en) Sparse depth map densing method and device
CN110148179A (en) A kind of training is used to estimate the neural net model method, device and medium of image parallactic figure
KR101971791B1 (en) System for providing of augmented reality in indoor space using visible light communication and the method thereof
JP6409433B2 (en) Image generation apparatus, image detection system, and image generation method
KR102107021B1 (en) Method, system and non-transitory computer-readable recording medium for providing an identification of data
CN113168729B (en) 3D shape matching method and device based on local reference coordinate system
JPWO2018207282A1 (en) Object recognition method, apparatus, system, program
JP6351350B2 (en) 3D model retrieval system and 3D model retrieval method
KR20180078115A (en) Method and apparatus for processing image
JP7224592B2 (en) Information processing device, information processing method, and program
JP2015219868A (en) Information processor, information processing method and program
JP6079076B2 (en) Object tracking device and object tracking method
JP2009288917A (en) Information processor, information processing method and program
JP6396353B2 (en) Determination apparatus and determination method

Legal Events

Date Code Title Description
A201 Request for examination
E902 Notification of reason for refusal
AMND Amendment
E601 Decision to refuse application
AMND Amendment
X701 Decision to grant (after re-examination)