JP2003077011A - Display method and device for three-dimensional shape model - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system capable of composing computer graphics and photographic image with high operatability. SOLUTION: This image composing device for composing the computer graphics and the photographic image comprises a means 1 for extracting a specific area in the photographic image, a means 2 for adding the three-dimensional shape information to the extracted area, and a means for computer graphic- modeling the information relating to the extracted area on the basis of the information on the extracted area and the information on the three-dimensional shape.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for synthesizing computer graphics and a real image.

[0002]

2. Description of the Related Art Recently, computer graphics (hereinafter referred to as CG) and synthesis of live-action video have been widely used in the production of movies and commercial films. For example, by synthesizing a live-action image of a human previously taken on a fictional building created with CG, it is possible to create the effect that a human is walking through the building. The image created by synthesizing this CG and the live-action image is real and has a strong impact on the viewer, and is especially indispensable for landscape simulation.

Generally, the shape of an object drawn in CG is
It is defined using simple geometric shapes (shape primitives) such as planes and quadric surfaces, and the surface is colored as desired and image data is pasted. However, with this method, when drawing natural objects such as trees and rivers, the figure always looks fixed. Therefore, we photographed in advance the trees swaying in the wind or the river in which water was flowing, and CG
A more natural animation can be created by synthesizing the live-action image with the scene created in. In the conventional method, an image is selected from a photographed live-action image and is attached to a simple shape primitive such as a flat plate to perform compositing processing with CG. This compositing process is repeated for each frame to produce a continuous composite image animation.

As a publicly known document regarding a composite image of a still image, "A method for constructing a 2.5-dimensional simple scene model for landscape simulation" (July 1992: "Image recognition /
There is an understanding of Symbodium (MIRU '92). In addition, Japanese Patent Application Laid-Open No. Sho 62-62 discloses a three-dimensional figure extraction which is a part of the present invention.
-162173 and JP-A-3-244005.

[0005]

In this type of technique, there are the following problems to be solved. (1) Easy conversion of a live-action video into a CG model having a three-dimensional shape (2) Allowing operator intervention during this conversion (3) Enabling composition (4) Operability when extracting the required parts from the live-action video,
Improve efficiency (5) Improve operability of rotation, scaling and movement of CG model (6) Make it easy to synchronize the synthesis of CG and live-action video

[Outline of the Invention] The method proposed by the present invention,
In the device (system), the computer interacts with the user using the image processing technique to 1) separate the image information into object units, 2) generate a moving image object with 3D geometric information, 3 ) Performs three processes: simultaneous display of CG model and moving image object. 1) makes it possible to take a blue back shot in the studio, 2) makes it unnecessary to measure or record the position information of the camera at the time of image shooting, and 3) makes it possible to change the viewpoint at the time of display.

Outline of System Configuration FIG. 1 shows an outline of the configuration of the system of the present invention. This system is composed of three processing units: a specific object area extraction unit, a three-dimensional geometric information extraction unit, and a moving image object and CG simultaneous drawing unit. The specific object area extraction unit and the three-dimensional geometric information extraction unit create data called a moving image object to be combined with the CG and store it in the hard disk. This data is used to create a video object and
The CG simultaneous drawing section generates a composite image in non-real time.

Specific Object Area Extraction Section The specific object area extraction section cuts out the area of the specific object from the video information input by the capturing tool. The flow of this processing is shown in FIG. Here, a continuous image sequence is received as input data, and as an output, an image sequence of a rectangular area including a specific object and an alpha map sequence storing an alpha value of the same size are created. If the object area is divided by a binary mask, unnatural aliasing occurs at the boundary. To prevent this, the area is defined by using the alpha value. After the area of the specific object is determined by the interactive process with the user for a certain n-th image, the n + 1 to n + m-th process is semi-automatically performed by the computer using the processing result of the previous frame.

3D Geometric Information Extraction Unit The 3D geometric information extraction unit uses the image sequence of the rectangular area including the specific object created by the specific object area extraction unit and the alpha map sequence to generate the 2D information. 3D geometrical information is extracted from the image information of. The extraction of this three-dimensional geometric information allows the user to transform, rotate, and transform a plurality of simple shape primitives (such as a rectangular parallelepiped) into an object on a two-dimensional image.
It is realized by performing fitting with the operation such as moving. This system extracts not only viewpoint information but also shape information of objects and texture images attached to each surface. In order to create a data structure called a moving image object, this extraction unit gives three-dimensional geometric information to an object in a video, extracts the video information sticking to each surface of the CG modeled object, and views it from the front. Normalize and store it.

Structure of Moving Image Object The data generated through the processing of the specific object region extracting unit and the three-dimensional geometric information extracting unit has a structure called a moving image object. FIG. 3 shows an outline of the structure of the moving image object.
The video object is a new data structure created to combine CG and video, and as surface information in addition to shape data,
It stores pointers to video information (still images or moving images) that stick to each surface.

Synthetic image generation unit The synthetic image generation unit simultaneously draws the generated moving image object data and CG data. At this time, the time T _i and the time interval Δt of the CG scene to be drawn are specified as the meta information. The CG data includes position information at each time in addition to the shape data of each object. Further, at time T _i , the image to be attached to each surface is selected from the image data in the moving image object. After the surface attributes of the object at time T _i are determined, a composite scene at time T _i is generated.

The present invention will be specifically described below. The invention of the present application can be roughly divided into two. (1) Overall configuration (2) Specific object area extraction section and 3D shape information addition section

(2) 2-1 Concerning the structure of the extraction unit of the specific object area and the addition unit of the three-dimensional shape information 2-2 Concerning the structure of the extraction unit 2-3 Concerning the display of the three-dimensional shape model 3 It is divided into two. In the following (1), the invention of the first group, 2-1,
2-2 and 2-3 are called inventions of the second, third and fourth groups, respectively.

Although the subject matter of the present application is the fourth group of inventions, the inventions of the first to third groups related thereto are also described. The first group of inventions will be described in detail. [Invention of the First Group] (Outline) The invention of the first group relates to an overall configuration of composition of CG and a live-action image.

[0015]

[Prior Art and Problems to be Solved by the Invention] When synthesizing a CG and a live-action image, the image after the synthesization is supposed to be taken,
The technique was to cut out only the part to be combined from the live-action image and overlay it on CG. In the case of shooting with such a method, a large-scale environment is required, such as studio shooting with blue background or measurement of the camera position during shooting.

The method supported by a computer is also the MIRU mentioned above.
Proposed in the '92 literature. This extracts viewpoint information from a live-action video, approximates the object in the video to a plane,
This is a method of combining with CG. However, since it is not a model that has complete three-dimensional information, the viewpoint cannot be changed at the time of composition, and the composition processing is limited. Japanese Patent Laid-Open No. 3-138784 discloses that an object in a still image is reconstructed based on a three-dimensional model in order to treat the object in the still image as three-dimensional.
A method has been proposed in which a partial image corresponding to a three-dimensional object is mapped and displayed as a surface texture of a three-dimensional object model. In this method, it is also proposed to synthesize a surface texture from a plurality of input images for one three-dimensional portion. However, in the case of a video (moving image), the surface texture may change every moment, and when a plurality of textures are combined, a texture smoothed in the time series direction may be obtained, which is unsuitable.

[0017]

The present invention has been made under such a technical background, and proposes an image synthesizing method capable of easily converting a photographed image into a CG model having a three-dimensional shape. The first purpose is to do so. A second object is to provide a video synthesizing method that can generate the CG model for each frame and, as a result, create a moving image.

[0018]

An image synthesizing method according to the present invention is an image synthesizing method for synthesizing computer graphics and a live-action video, and a process of extracting a specific area in the live-action video The main features are that it includes a process of adding information of a three-dimensional shape and a process of computerizing information on the extraction region based on the information of the extraction region and the information of the three-dimensional shape.

Further, there is provided a step of synthesizing the computer graphics modeled information relating to the extraction area and another computer graphics model so as to be mixedly displayed. Then, the same processing is executed over a plurality of frames to create a moving image.

An image synthesizing device according to the present invention is a device for synthesizing computer graphics and a live-action video, and means for extracting a specific region in the live-action video,
A main feature is that it is provided with means for adding three-dimensional shape information to the extracted region, and means for computerizing the information related to the extracted region into a computer graphics model based on the extracted region information and the three-dimensional shape information. To do.

Further, there is provided means for synthesizing the computer graphics modeled information relating to the extraction area and another computer graphics model so as to display them together.

A region corresponding to a specific object is cut out from a real image and three-dimensional shape information is added to this. As a result, a CG model having the surface attribute of the specific object of the live-action image is generated. It can be used alone or mixed with other CG models. Further, by performing the same processing over a plurality of frames, it is possible to combine images in a moving image.

[0023]

BEST MODE FOR CARRYING OUT THE INVENTION The present invention will be specifically described below with reference to the drawings showing the embodiments thereof. FIG. 4 is a block diagram of an apparatus for carrying out the method of the present invention, and FIG. 5 is a flow chart of the processing. In FIG. 4, reference numeral 9 denotes an image supply device such as a TV camera, a video tape, a video disk, etc., and the actually-photographed image information obtained from these is stored in each frame in the image storage unit 5 including a video memory. The photographed image information stored in the image storage unit 5 is given to the specific object region extraction unit 1, where the region of a specific object in the photographed image is extracted. The operator designates the extraction area using a pointing device 12 such as a mouse. The specific contents thereof are detailed in the description of the inventions of the second to fourth groups. FIG. 6 shows a case where a quadrangular prism and a three-sided pyramid are displayed as a live-action image.
The state is shown when a prism is designated as an extraction region (shown by a thick line). The image information of the area designated in this way is sent to the three-dimensional shape information adding unit 2, where the three-dimensional shape information is added and stored in the shape / surface attribute information storage unit 6.

The three-dimensional shape information addition section 2 adds three-dimensional shape information to the information given from the specific object area extraction section 1 and stores it in the shape / surface attribute information storage section 6. The specific configuration of the three-dimensional shape information adding unit 2 is detailed in the invention of the second group, but here again, one example will be described.

FIG. 7 is a flowchart thereof. First, as shown in FIG. 8, an area or object that is designated and extracted is displayed on the screen of the image display device 10 and the operator is prompted to input the focal length f of the image (S1). A character / numeric input device 11 such as a keyboard is used for this input. Next, the ridge line is drawn on the screen by using the pointing device 12, and the depth value is input (S2). In FIG. 8, the drawn ridge line is indicated by a thick line, and the designated depth value is indicated by Z. This drawing and depth designation can be canceled and corrected. Since the surface can be specified basically by a triangle (three ridges), the present invention also draws ridges so as to divide into triangles as shown in FIG. 9, and assists in dividing into triangles. Draws a line (diagonal rectangle), and two different ridgelines (including auxiliary lines) do not intersect and all points in the extraction area are surrounded by three ridgelines. It is in the state of being on (S3).

Next, the three-dimensional coordinates of the end points are calculated (S4).
This is obtained by X = (x / f) × Z Y = (y / f) × Z based on the focal length f input in S1 and S2, the depth Z, and the coordinates (x, y) on the image of the end point. . The three-dimensional coordinates of the point on the ridgeline and the point in the area surrounded by the ridgeline can be calculated by the following formula.

The three-dimensional coordinates of the end points of the ridge and the coordinates on the image are respectively
(X _i , y _i ), (X _i , Y _i , Z _i ) (i = 1, 2)
Then, the three-dimensional coordinates (X, y) of the point (x, y) on the edge line
Y, Z) is obtained by X = (1-t) X 1 + tX 2 Y = (1-t) Y 1 + tY 2 Z = (1-t) Z 1 + tZ 2. However, when t is x ₁ ≠ x ₂ , t is (x−
x ₁ ) / (x ₂ −x ₁ ), and when x ₁ = x ₂ , (y−y)
₁ ) / (y ₂ −y ₁ ).

Points in Region Surrounded by Ridges All points in this region are surrounded by three ridges,
Their intersections are guaranteed to be the endpoints of the three ridges. Therefore, the plane formed by the coordinates of the three intersections can be obtained from the coordinates (X _i , Y _i , Z _i ) of the three intersections (i = 1, 2, 3) (obvious). Letting the equation of this plane be aX + bY + cZ-1 = 0, the three-dimensional coordinates (X, Y, Z) of the coordinates (x, y) on the image of the points in the area are: X = x / (ax + by + cf) Y = y / (ax + by + cf) Z = f / (ax + by + cf)

From the ridge thus obtained, the three-dimensional coordinates of the end points and the connection relation are shape information, and the coordinate correspondence of the end points on the specific object area and the image data of the specific object area image are the surface attribute information. .Surface attribute information storage unit 6
Store in (S5). Table 1 shows the stored contents of the shape / surface attribute information storage unit 6. The above steps S1 to S5 are repeated for all frames (S6).

[0030]

[Table 1]

Next, the contents of the shape / surface attribute information storage unit 6 are converted into a CG model by the video CG model generation unit 3. CG of shape information
Regarding modeling, it is possible to generate a CG model as it is by regarding the end points as vertices, the ridge lines as sides, and the enclosed parts as faces based on the connection relationship of the ridge lines and the three-dimensional coordinates.

On the other hand, regarding the surface attribute information, the image information corresponding to the position is used as the texture of the generated CG model as the surface attribute information of the portion regarded as the surface. At that time, the image information is normalized as an image viewed from the normal direction in a three-dimensional space. The rotation matrix R for normalization is given by the following equation.

[0033]

[Equation 1]

However, the rotation angle ψ and the rotation angle κ are based on a, b, and c when the equation of the plane of this region is expressed as aX + bY + cZ-1 = 0.

[0035]

[Equation 2]

It is The values a, b, and c can be obtained from the three-dimensional coordinates (X _i , Y _i , Z _i ) (i = 1, 2, 3) of the three vertices. Such a CG modeling process is applied to all frames, and a CG model for a live-action video is acquired as a CG model sequence for each frame and stored in the video CG model storage unit 7b. The CG model creating unit 13 creates a normal CG model, which is not created from the above-described photographed image, and the created CG model is stored in the CG model storage unit 7a.

The composite information storage unit 8 stores the information (CG model layout information) for combining the CG model and the video CG model created from the photographed image in the composite image generation unit 4, and generates the composite image. Based on this, the section 4 synthesizes both CG models and displays them on the image display device 10,
Alternatively, it is recorded on a recording medium (not shown). The composite image generation unit 4 and the composite information storage unit 8 are detailed in the fifth group of inventions.

[0038]

In the case of the present invention as described above, since the photographed image is converted into a CG model having a three-dimensional shape, a normal CG
It can be handled in the same way as the model, and processing such as composition can be performed easily. Then, the CG model of the photographed image can be obtained by a simple operation of extracting a region and adding three-dimensional shape information thereto. Further, at this time, since the operator can manually intervene, delicate adjustment or this artificial change can be performed, and the degree of freedom is increased. Also, it can be applied to a moving image by processing a plurality of frames in the same manner.

[Invention of Second Group] (Outline) The present invention relates to the configurations of the specific object area extracting section 1 and the three-dimensional shape information adding section 2 of FIG.

[0040]

2. Description of the Related Art A method for completely extracting the shape of a three-dimensional object in an image has not been established yet. Proposed as a conventional technique is to assume the reflection characteristics of the object surface and store the model of the object observed in the image in advance and the method of obtaining the inclination of the object surface from the observed color value. A method of matching the appearance of an object observed in a model and an image, and so on. These have been developed with the development of image understanding research.

However, neither method can be applied unless the application conditions are met. For example, the former method cannot be applied to an object whose reflection characteristics cannot be assumed, and the latter method cannot be applied to a model object that is not stored. Therefore, in the present invention, when a three-dimensional shape of an object included in an image is obtained, a human specifies a rough shape of the object, a model of the shape is displayed on an image, and a superimposing method is specified by a human. It is an object of the present invention to provide a three-dimensional shape extraction method and apparatus that interactively perform automatic adjustment by a computer using an image processing method alternately.

[0042]

The method of the second group of inventions comprises:
In a method of extracting a three-dimensional shape of an object included in a live-action image, a process of preparing data of a plurality of geometric shapes in advance and a process of extracting a region corresponding to the object from the live-action image are extracted. A process of selectively displaying one of the shapes according to the data on the screen displaying the area,
The position of the shape to match the region and shape,
And a process of adjusting the direction and the size.

The device of the second group of inventions is a device for extracting the three-dimensional shape of an object included in a live-action image, and means for preparing data of a plurality of geometric shapes in advance, Means for extracting a region corresponding to the object,
A means for selectively displaying any shape according to the data on a screen displaying the extracted area, and an adjusting means for adjusting the position, orientation, and size of the shape so as to match the area and the shape. Is characterized by.

The adjusting means is provided with automatic adjusting means for position, orientation and size based on the shape and hue value of the object.
Further, it is provided with means for mapping the image information of the area extracted from the photographed image on the adjusted shape.

A shape close to the area of the extracted object is selected and displayed from the shapes prepared in advance. Then, this region and the shape are adjusted so as to match, and the three-dimensional shape of the target object can be extracted. This result is similar to the result obtained by the three-dimensional shape information adding unit 2 described above.

[0046]

BEST MODE FOR CARRYING OUT THE INVENTION The second group of inventions will be described in detail below with reference to the drawings showing the embodiments thereof. FIG. 10 is a block diagram of a three-dimensional shape extraction device. In the figure, reference numeral 21 denotes an object area extraction unit, which extracts an area of a desired object from a real image and displays it on the image display device 27. This is detailed in the invention of the third group. The photographed image and the extracted image are stored in the image storage unit 25. The basic shape selection unit 22 stores a large number of basic shape patterns as shown in FIG. 12, and the operator selects the pattern and displays it on the image display device 27. The basic shape superposition unit 23 displays the pattern of the basic shape selected by the operator and the image of the extracted object as shown in FIG.
As shown in FIG. 5, the two are displayed in a superimposed manner, and the both are matched by the operation of the operator and the automatic adjustment by the computer as described later. The result of overlapping so as to match is stored in the overlapping information storage unit 26. The overlay result display unit 24 maps the image information of the surface of the extracted object on the adjusted basic shape.

Next, the three-dimensional shape extraction method will be described with reference to FIG. The real image stored in the image storage unit 25 is taken out and displayed on the image display device 27 so that the object area extraction unit
The required object is extracted at 21 (S21). FIG. 14 is an explanatory diagram of this operation. The operator draws a closed curve exemplifying the object area and the background area on the screen by using the drawing device. The object area extraction unit 21 expands the closed curve of the object area and contracts the closed curve of the background area. This expansion and contraction is recognized only in the portions having similar hues. Then, the two closed curves come into contact with each other at the boundary, whereby the boundary is specified and the desired object region is extracted. As shown in Fig. 14 (b), as a result of expansion and contraction, the border may be recognized as thick due to the presence of a shadow, etc. In this case, the inner line of the thick border is set as the boundary of the object.

Next, the pattern of the basic shape (shape primitive) is displayed by performing a predetermined operation, and a pattern similar to the shape of the extracted object is selected (S22). As a result, the images are overlaid and displayed as shown in FIG. 13 (S23). Generally, the extracted object shape does not match the selected basic shape. Therefore, until both match (S24), position adjustment (S27), orientation adjustment (S28), and size adjustment are performed for the object shape and basic shape.
(S29) and partial deformation of the shape (S30) are performed. Match / mismatch depends on the operator's judgment.

FIG. 15 is a flow chart of processing relating to position movement, and FIG. 16 is an explanatory diagram thereof. The principle of this movement is to match the center of gravity of the wire frame of the shape primitive with that of the object region. That is, calculation of the center of gravity G _RO of the object area (S31)
, And the center of gravity of the wireframe of the shape primitive G _RP
Is calculated (S33). Then, move the wireframe display position of the shape primitive to match them.
(S32).

The wireframe display position of the shape primitive is moved so that the barycenter R _{RO of the} object area and the barycenter R _{RP of the} area surrounded by the wireframe display of the shape primitive match (FIG. 16). The center of gravity G _{R of the} region R can be obtained by G _R = (m ₁₀ / m ₀₀ , m ₀₁ / m ₀₀ ) ^T. However, m ₀₀ m ₀₀ = ∫fdR Indicates the number of points forming the region R. This value represents the area. m ₁₀ m ₁₀ = ∫xdR Shows the sum of the x-coordinates of each point forming the region R. m ₀₁ m ₀₁ = ∫ ydR Indicates the sum of y coordinates of the points forming the region R. In accordance with this, the wireframe display position of the shape primitive is moved (G _RO -G _RP ).

FIG. 17 is a flowchart showing the processing of rotating the shape primitive for adjusting the orientation, and FIG. 18 is an explanatory diagram thereof. The principle of orientation adjustment by rotation lies in the parallelization of the long axes of the object region and the wireframe of the shape primitive. The major axis direction θ _R of the region _R can be obtained as the principal axis of inertia around the center of gravity of the region. That is, tan ² θ _R + [{m ₂₀ −m ₁₀ / m ₀₀ ) − (m ₀₂ −m ₀₁ /
m ₀₀ )} / (m ₁₁ −m ₁₀ m ₀₁ / m ₀₀ )] tan θ _R −1 =
It can be obtained as a solution of 0. However, m ₁₁ m ₁₁ = ∫xydR indicates the sum total value of the products of the x-coordinate and the y-coordinate of each point forming the region R. m ₂₀ m ₂₀ = ∫x ² dR Shows the sum of squares of the x-coordinates of the points forming the region R. m ₀₂ m ₀₂ = ∫y ² dR Shows the sum of squares of the y-coordinates of the points forming the region R.
According to this, the wireframe display position of the shape primitive is rotated by (θ _RO −θ _RP ).

As shown in the flow chart of FIG. 17, the amount of moment of the wire frame of the extracted object region and shape primitive is calculated (S41, S44). The calculation of this moment amount is m _ij = ∫x ⁱ y ^j dR (ij) = {(0,0), (1,0), (0,1), (1,1), (2,0), (0,2)}.

On the other hand, as described above, the long axis of the object region,
And shape primitive wireframe long axis and weight
Heart G_RPIs obtained as described above (S42, S45, S46). That
G _RPCentered on θ_RO-R_RPOnly of shape primitives
Rotate the wireframe display position (S43).

As shown in FIG. 20, the size is adjusted by enlarging or reducing the wireframe of the shape primitive around the center of gravity G _RP of the region R _P so that their display areas coincide with each other. That is, the area S _{R of the} region R can be obtained as S _R = m ₀₀ . Accordingly, the wireframe of the shape primitive may be multiplied by S _RO / S _RP . Here, S _RO is the area of the object region S _RP is the area of the wireframe of the shape primitive.

In the flowchart of FIG. 19, the moment amount of the extracted object region and the moment amount of the wire frame display region of the shape primitive are calculated (S51, S54).
. Then, using this, the areas S _RO and S _RP of both are calculated (S52, S55). Also, the center of gravity G _RP of the wire frame of the shape primitive is calculated (S56). Then, the wireframe of the shape primitive is multiplied by S _RO / S _RP (S53). The area can be obtained as the moment amount m ₀₀ .

Returning to FIG. 11, the deformation of the shape will be described. When the shape of the object region is partially different from the basic shape, the basic shape is partially deformed by a command input by the operator. When the object region and the basic shape match as described above, this is stored in the overlay information storage unit 26 (S25).
. Then, as shown in FIG. 21, the image information of the extracted object region is mapped to the wire frame of the shape primitive (S26). In other words, the required part of the real image is cut out and attached to the wireframe of the shape primitive.

[0057]

In the case of the second group of inventions as described above, the operator can extract the three-dimensional shape in an interactive manner, so that the application conditions are not restricted and the known information (reflection information etc.) for the object is required. It is possible to extract without doing.
Further, since the computer automatically performs the work of matching the basic shape with the object area, the burden on the operator is light.
In addition, since the mapping is performed, the suitability of the extracted three-dimensional shape information can be intuitively determined.

[Invention of Third Group] (Outline) The invention of the third group is based on the specific object area extracting unit or the drawing of FIG.
The present invention relates to 10 object area extracting units.

[0059]

2. Description of the Related Art An image is electrically synthesized as shown in FIG. For example, an image of a person image is photographed by the image input section A with a blue background, and a landscape image is photographed by the image input section B. Then, the blue component is detected from the image of the image input unit A, the blue component is inverted and amplified, and the mixing ratio is appropriately controlled, and the inverted amplified signal and the image input units A and B are detected.
The signal from is combined with a mixing amplifier and output to the image output unit. As a result, the background from the image input section A disappears, and the person image with the image input section B as the background is synthesized.

[0060]

However, such a conventional method requires a blue background and is burdensome in terms of equipment. In addition, since only those intended for image composition can be used from the beginning, they lack versatility. Furthermore, it is difficult to set parameters for synthesis in the mixed amplifier, and the operation is complicated. The present invention has been made to solve such a problem,
An object of the present invention is to provide an image synthesizing device that does not require special photographing equipment, has high versatility, and is easy to operate, and in particular, a device for generating a key image to be synthesized.

[0061]

According to a first method of the third group of inventions, in a method of extracting a specific area from an image, a process of designating a plurality of pixels in an area to be extracted,
A process of obtaining a predetermined feature amount in a specified pixel, a process of obtaining the maximum value and the minimum value of the obtained feature amount, a feature amount of pixels inside and outside an area to be extracted, and the feature amount And a step of selecting a pixel between a maximum value and a minimum value, and an area constituted by the pixels is set as an extraction area.

A second method is a method of extracting a specific area from an image, a step of designating a plurality of pixels in the area to be extracted, and a step of obtaining a predetermined feature amount in the designated pixel, The process of calculating the difference between adjacent pixels for the obtained feature amount of the specified pixel, the process of obtaining the maximum value of the calculated difference, and the difference in the feature amount between the adjacent pixels starting from the specified pixel And a process of connecting pixels in four neighborhoods or eight neighborhoods that are smaller than the maximum value, and a region formed by the joined pixels is set as an extraction region.

A third method is a process of assigning different values to the pixels of the extraction area and the pixels of the non-extraction area, and the pixel located at the outer edge of the boundary of the extraction area has an intermediate value of the values. And a step of giving a value, and generating an image with these added values.

In the fourth method, a different intermediate value is given to each of a plurality of pixels adjacent to each other in the direction away from the extraction area.

A fifth method is a method of extracting a specific area from an image, a step of specifying a plurality of pixels in an area to be extracted, and a step of obtaining a predetermined feature amount in the specified pixel, The process of obtaining the maximum value and the minimum value of the obtained feature amount, and the feature amount is obtained for pixels inside and outside the region to be extracted, and whether the feature amount is in the range between the maximum value and the minimum value. A step of determining whether or not, a step of giving a constant K to the pixels within the range, a step of calculating a difference between the feature amount of the pixel outside the range and the maximum value or the minimum value,
A step of giving a value obtained by subtracting a value determined in relation to the difference from a constant K to pixels outside the range, and generating an image with these given values.

A sixth method is a method of extracting a specific area from an image, a step of designating a plurality of pixels in an area to be extracted and a step of obtaining a plurality of predetermined feature quantities in the designated pixel. And a process of obtaining the maximum value and the minimum value of the obtained feature amount for each of the feature amounts, and the feature amount is obtained for pixels inside and outside the region to be the extraction target, and the feature amount is the maximum value and the minimum value. A step of determining whether or not there is a range, a step of assigning a constant K to the pixels within the range, and a step of calculating the difference between the feature amount of the pixel outside the range and the maximum value or the minimum value. And a step of giving a value obtained by subtracting a value determined in relation to the difference of each feature amount from a constant K to pixels outside the range, and generating an image with these given values. And

A seventh method is a method of extracting a specific area from an image, a step of designating a plurality of pixels in an area to be extracted, and a step of obtaining a predetermined feature amount in the designated pixel. The process of obtaining the average value and variance of the obtained feature amount, and the feature amount is obtained for pixels inside and outside the region to be extracted, and it is determined whether the feature amount is within the range defined by the average value and variance. A step of giving a constant K to the pixels within the range, a step of calculating a deviation between the feature value of the pixel outside the range and the average value, and a deviation of the constant K from the constant K to the pixel outside the range. And a step of giving a value obtained by subtracting a value determined in association with the above, and generating an image with these given values.

The eighth method is a method of extracting a specific area from an image, a step of designating a plurality of pixels in an area to be extracted and a step of obtaining a plurality of predetermined feature quantities in the designated pixel. And a process of obtaining the average value and variance of the obtained feature amount for each feature amount, and obtaining the feature amount for pixels inside and outside the region to be the extraction target, the feature amount falls within the range determined by the average value and variance. A step of determining whether or not there is a pixel, a step of giving a constant K to the pixels within the range, a step of calculating a deviation between the feature amount of the pixel outside the range and the average value, and a pixel outside the range And a step of giving a value obtained by subtracting a value determined in relation to the deviation of each feature amount from the constant K, and generating an image with these given values.

The ninth method is a process of designating a pixel included in any one of a plurality of regions extracted from an image, and a process of labeling 4 or 8 connections with the designated pixel as a starting point. And a step of changing an unlabeled area into a non-extracted area.

The tenth method is a method of extracting a specific area from a video of a plurality of frames, and a process of specifying a plurality of pixels in an area to be extracted in one frame and a start point of the specified pixel. As a 4-connected or 8-connected labeling, a process of changing an unlabeled region into a non-extracted region, and a process of calculating a geometric feature amount of the extracted region, and labeling in the next frame. The process, the process of calculating the geometric feature amount for each region with different labels, and the region having the geometric feature amount close to the geometric feature amount of the extraction region of the previous frame is left as the extraction region. , And a step of changing another area to a non-extracted area.

The eleventh method is a method of extracting a specific area from a video of a plurality of frames, and a process of specifying a plurality of pixels in an area to be extracted in one frame, and a start point of the specified pixel. And a process of labeling unconnected regions into non-extracted regions and a process of calculating the optical feature amount of the extracted regions, and labeling in the next frame And a process of calculating the optical feature amount for each region to which different labels are given, and a region having an optical feature amount close to the optical feature amount of the extraction region of the previous frame is left as the extraction region, and the other regions are To a non-extracted area.

The first device is a device for extracting a specific area from an image, a means for designating a plurality of pixels in the area to be extracted, a means for obtaining a predetermined feature amount in the designated pixel, A means for obtaining the maximum value and the minimum value of the obtained feature amount, a means for storing the maximum value and the minimum value, and a feature amount for pixels inside and outside the region to be extracted, and the feature amount is Means for selecting a pixel between a maximum value and a minimum value, and an area constituted by the pixels is set as an extraction area.

The second device is a device for extracting a specific area from an image, a means for specifying a plurality of pixels in the area to be extracted, a means for obtaining a predetermined feature amount in the specified pixel, A means for calculating a difference between adjacent pixels for the obtained feature amount of the designated pixel, a means for obtaining a maximum value of the calculated difference, and a means for storing the maximum value,
A specified pixel as a starting point, means for connecting pixels in four or eight neighborhoods in which the difference in feature amount between adjacent pixels is smaller than the maximum value, and a region formed by the connected pixels is defined as an extraction region. The feature is that it is done.

The third device is a means for giving different values to the pixels of the extraction area and the pixels of the non-extraction area, and the pixel located at the outer edge of the boundary of the extraction area has an intermediate value of the values. Is provided to generate an image with these added values.

The fourth device is designed to give different intermediate values to each of a plurality of pixels adjacent to each other in the direction away from the extraction area.

A fifth device is a device for extracting a specific region from an image, a device for designating a plurality of pixels in the region to be extracted, and a device for obtaining a predetermined feature amount in the designated pixel. A means for obtaining the maximum value and the minimum value of the obtained feature amount, a means for storing these maximum value and the minimum value, and a feature amount for the pixels inside and outside the region to be extracted, and the feature amount is the maximum value. And a minimum value, and a constant K for pixels in the range.
Means for calculating the difference between the feature amount of the pixel outside the range and the maximum value or the minimum value, and for the pixel outside the range subtracting the value determined in relation to the difference from the constant K. It is characterized in that it is provided with means for giving different values to generate an image with these given values.

A sixth device is a device for extracting a specific area from a video, and means for designating a plurality of pixels in the area to be extracted and means for obtaining a plurality of predetermined feature quantities in the designated pixel. A means for obtaining the maximum value and the minimum value of the obtained feature amount for each feature amount, a means for storing the maximum value and the minimum value, and obtaining the feature amount for pixels inside and outside the region to be extracted. , Means for determining whether or not the feature amount is in the range between the maximum value and the minimum value, means for assigning a constant K to pixels within the range, and feature values for pixels outside the range. A means for calculating a difference from the maximum value or the minimum value, and means for giving to the pixels outside the range a value obtained by subtracting a value determined in relation to the difference of each feature amount from a constant K, To generate an image with the value given by And wherein the Rukoto.

A seventh device is a device for extracting a specific region from a video image, and means for designating a plurality of pixels in the region to be extracted, and means for determining a predetermined feature amount in the designated pixel, A means for obtaining the average value and the variance of the obtained feature amount, a means for storing the average value and the variance, and a feature amount for pixels inside and outside the region to be extracted,
A means for determining whether or not the feature amount is within a range determined by the average value and the variance, a means for giving a constant K to pixels within the range, and a feature amount and an average value for pixels outside the range. A means for calculating the deviation and a means for giving a value obtained by subtracting a value determined in relation to the deviation from the constant K to the pixels outside the range are provided to generate an image with these given values. It is characterized by being.

The eighth apparatus is an apparatus for extracting a specific area from a video image, and means for designating a plurality of pixels in the area to be extracted and means for obtaining a plurality of predetermined feature quantities in the designated pixel. A means for obtaining the average value and variance of the obtained feature amount for each feature amount, a means for storing the average value and variance, and a feature amount for pixels inside and outside the region to be extracted, Means for determining whether or not the amount is in a range determined by the average value and variance, means for giving a constant K to pixels within the range, and deviation between the feature amount of pixels outside the range and the average value And means for giving to the pixels outside the range a value obtained by subtracting a value determined in relation to the deviation of each feature amount from the constant K, and generating an image with these added values. Characterized by what is done .

A ninth apparatus is a means for designating a pixel included in any one of a plurality of areas extracted from an image, and a means for labeling four or eight connections with the designated pixel as a starting point. And means for changing an unlabeled area into a non-extracted area.

The tenth apparatus is, in an apparatus for extracting a specific area from a video of a plurality of frames, a means for designating a plurality of pixels in an area to be extracted in one frame and a starting point for the designated pixel. 4 means or 8 means labeling, means for changing an unlabeled area to a non-extraction area, and means for calculating a geometric feature amount of the extraction area, and labeling in the next frame Means, a means for calculating the geometric feature amount for each region to which different labels are given, and a region having a geometric feature amount close to the geometric feature amount of the extraction region of the previous frame is left as the extraction region. , And means for changing another area to a non-extracted area.

The eleventh apparatus is, in an apparatus for extracting a specific area from a video of a plurality of frames, a means for designating a plurality of pixels in an area to be extracted in one frame and a starting point for the designated pixel. Means for performing 4-connection or 8-connection labeling, means for changing an unlabeled area into a non-extraction area, and means for calculating an optical characteristic amount of the extraction area, and means for labeling in the next frame And a means for calculating an optical feature amount for each region to which a different label is given, and a region having an optical feature amount close to the optical feature amount of the extraction region of the previous frame is left as an extraction region, and another region To a non-extracted area.

In the first method and apparatus, a plurality of pixels in an image portion to be extracted are designated (traced with a light pen or a cursor operated by a mouse). The feature quantity (one or more of R, G, B, hue, saturation, brightness, brightness, etc.) in the traced pixel group is obtained, and the maximum value and minimum value thereof are selected and stored.

Then, it is checked whether or not each feature amount is within the range of the maximum value to the minimum value for the pixels of the entire image. Pixels within the range have the same feature amount as the image portion desired to be extracted, so it is determined that the image portion belongs, a value greater than 0 is given, and pixels outside the range are non-extracted portions. 0 is given as. As a result, a desired image portion can be extracted by extracting the non-zero portion.

In the second method and apparatus, the difference between the characteristic amount of the traced pixel and the characteristic amount of the adjacent pixel is obtained, and the maximum value is stored. Pixels near 4 or 8 having a difference less than or equal to this maximum value are given a value larger than 0 as an extraction area, assuming that they have a threshold value of adjacency that is similar to that of the area desired to be extracted, and other areas. Gives 0. As a result, the non-zero portion can be extracted.

In the third method and apparatus, when 1 is given to the extraction area and 0 is given to the non-extraction area, the pixel at the boundary between them is given an intermediate value between 1 and 0. This makes the boundaries mild,
When the extracted images are combined, they blend well into the background.

In the fourth method and apparatus, the boundary is further made mild by setting a plurality of intermediate values.

The fifth method and apparatus adaptively control the mildness of the boundary, and determine the intermediate value of 1 to 0 by determining the feature amount of the non-extracted area and the maximum value (or minimum value) of the feature amount. Determined according to the difference between and. This allows the boundaries of the extracted image to blend well with the background.

The sixth method and apparatus use not only one kind of feature quantity but two or more kinds, obtain the above difference for a plurality of feature quantities, and determine an intermediate value based on, for example, a weighted average. Since a plurality of feature quantities are used, a more natural boundary can be obtained.

The seventh and eighth methods and apparatuses use the maximum value and the minimum value in the fifth and sixth methods, but are different in that the variance is used.

In the ninth method and apparatus, the excessively extracted portion is set as the non-extracted area. That is, by labeling, different codes are given to a plurality of similarly extracted regions. this house,
Only the area containing the traced pixel is left and the others are erased.

The tenth method and apparatus are for moving pictures. Labeling is performed in the same manner as in the ninth method and apparatus to erase the non-extracted area. The same labeling is performed in the next frame, but the region between the frames is identified based on the similarity of the geometric features. Therefore, only the extraction area remains and the others disappear. By performing this over a plurality of frames, the extraction process in the moving image can be automatically performed.

The eleventh method and apparatus use the optical feature amount instead of the above-mentioned geometric feature amount, and have the same effect.

[0094]

BEST MODE FOR CARRYING OUT THE INVENTION FIG. 23 is a block diagram of a first region extraction device of the third group of inventions. Image input section of 3 systems 31,3
Both 2, 33 have the same configuration, and NTSC-RGB converters 31a, 32a, 33a that convert NTSC signals to analog RGB signals and analog RGB signals to digital RGB signals.
Equipped with A / D converters 31b, 32b, 33b. These image input section 3
Inputs from 1, 32 and 33 are given to image memories 37, 38, 39 and 40 consisting of dual port RAM, and image data read from these are given to an image output section 34 and outputted from there. The image output unit 34 includes a D / A converter 34b for converting a digital RGB signal from the image memory 37 or the like into an analog RGB signal, and an NT / DC converter for converting the converted analog RGB signal.
The output of the RGB-NTSC converter 34a that converts to an SC signal is monitored
Will be displayed (not shown).

Reference numeral 35 is a coordinate input unit, which is composed of a light pen and its coordinate recognition means, and is used to trace a part of the image displayed on the monitor. The coordinate information input by the coordinate input unit 35 is input to the processing unit 41. 400 is a semiconductor memory, the memory used for calculation
42, and a feature amount upper limit register 43 and a lower limit register 44 described later. A large-capacity recording unit 36 such as a hard disk or a magneto-optical disk records images of a plurality of frames.

Thus, the processing unit 41 including a microprocessor or the like performs the following processing for area extraction. Figure 24
FIG. 25 is a flowchart showing the procedure of this process, and FIG. 25 is an explanatory diagram thereof. Area to be extracted as shown in Fig. 25 (a)
Trace (marked in white) with the pen of the coordinate input section 35. During this time, the feature quantity (one or more kinds) is calculated for a plurality of pixels of the pen locus. Then, the maximum value or the minimum value of the characteristic amount is stored in the characteristic amount upper limit register 43 and the lower limit register 44, respectively. This is done by updating the already stored register contents each time the pen moves. When the tracing is completed, the maximum and minimum values of the feature quantity in all trajectories will be obtained. Examples of the feature amount include R, G, B, hue, saturation, brightness, and brightness.

Then, next, the pixel dot feature amount of the entire screen
(One or a plurality of types) is calculated, and a value larger than 0 (for example, 255) is given to the pixels within the range of the maximum value to the minimum value, and 0 is given to the pixels outside the range. As a result, a key image, that is, an image including the extraction area is obtained. Figure 25
(b) shows this. If the desired extraction cannot be performed, it may be retried by changing the selection or combination of the feature amounts. It is possible to process a moving image by repeating the above process for a plurality of frames.

FIG. 26 is a block diagram of the second area extracting apparatus. A semiconductor memory is different from the first area extraction device.
The feature 400 is that a feature amount upper limit register 43 and a lower limit register 44 are replaced with a feature amount threshold value register 45. Since other configurations are similar, the same reference numerals are given and description thereof is omitted.

FIG. 27 is a flowchart of the processing by the processing unit 41, and FIG. 28 is its explanatory diagram. As in the case of the first device, the feature amount of the pixel of the locus traced by the pen as shown in FIG. 28 (a) is obtained, but the feature between adjacent pixels of the traced pixels is obtained in the second device. The difference between the quantities is calculated, and the maximum value is stored in the threshold value register 45. Then, for each traced pixel, it is checked whether or not the adjacent pixel (4 vicinity or 8 vicinity) is less than or equal to the threshold value, and the following adjacent pixels are connected one after another (FIG. 28 (b)). A value greater than 0 is given to the areas thus connected.

FIG. 29 is a block diagram of the third to sixth area extracting devices. The difference from the first apparatus is the calculation contents of the processing unit 41, and the mixing ratio calculation 41a and the total mixing ratio calculation 41b described below are performed. FIG. 30 is a flowchart showing the processing procedure of the processing unit 41. As shown in FIG. 31 (a), for the pixels of the locus traced by the pen, the feature amount is calculated in the same manner as in the first device, and the maximum value and the minimum value are respectively set in the feature amount upper limit register 43,
Put in the lower limit register 44.

Next, the feature amount is calculated for all pixels of the image, and it is checked whether or not this is within the range of the maximum value and the minimum value stored in the upper and lower limit registers 43 and 44 of the feature amount,
If it is within the range, a non-zero value K is given. If it is out of the range, the difference between the calculated feature amount and the maximum value (when the feature amount is large) or the difference between the calculated feature amount and the minimum value (when the feature amount is small) is calculated, and the difference is calculated. Depending on K
A value (mixing ratio) in the range of 0 is obtained for each feature amount. Then, the total mixture ratio is obtained by weighted averaging the mixture ratios for each feature amount. Then, a value according to the total mixture ratio is given to the corresponding pixel. Then, as shown in FIG. 31 (b), an extracted image with a gradation added to the boundary is obtained. Then, by repeating this for a plurality of frames, a moving image can be dealt with.

FIG. 32 is a block diagram of the third, fourth, seventh and eighth area extracting devices. The difference from FIG. 29 is that the feature amount upper limit register 43 and the lower limit register 44 are replaced with the feature amount average value register.
46, and a feature value variance value register 47 is provided. FIG. 33 is a flowchart showing the processing procedure in this case.
As shown in (a), the feature amount of the pixel traced by the pen is calculated, the average value and the variance value thereof are calculated, and these are stored in the feature amount average value register 46 and the feature amount variance value register 47. deep.

In this apparatus, it is checked whether the feature values of all the pixels in the image are within a predetermined deviation (for example, mean value ± dispersion value), and if it is within the range, K is given. If it is out of the range, the mixing ratio is calculated for each feature amount according to the deviation from the average value, the weighted average of the calculated values is obtained as the total mixing ratio, and K is given according to this.

FIG. 34B shows the result, and an extracted image having a gradation at the boundary is obtained. Figure 35 shows the third
4 is a block diagram of another embodiment of the region extraction device of No. 4 of FIG. This device is different from the other devices in the processing of the processing unit 41. The details of this processing will be described with reference to FIGS. In this embodiment, the outline (between pixels) between the extraction area and the non-extraction area (giving a value of 0) obtained by the first area extraction device or the like
A value obtained by subtracting a constant K from the value X of the inner peripheral contour point (pixel) on the inner side is given to the outer peripheral contour point (pixel) on the outer side of the contour. This processing may be performed only for one pixel in the centrifugal direction, but a smoother edge can be obtained by performing this processing for a plurality of pixels as shown in FIG.

FIG. 36 is a flowchart showing the procedure of this processing, and the processing is repeated so that the contour is traced from the upper left side on the screen. Then, by performing this process for a plurality of frames, it is possible to deal with a moving image.

FIG. 39 is a block diagram of the ninth area extraction device. This device is for removing noise, that is, a portion that appears as an extraction region when originally not desired to be extracted, by performing a labeling process (48) described later in the processing unit 41. This processing is performed on the key image (FIG. 41 (a)) obtained by, for example, the first area extracting device. This image contains a noise region (non-zero region) having the same feature amount other than the portion desired to be extracted in the center.

FIG. 40 is a flow chart of this processing.
In this processing, labeling of 4 or 8 connections is performed with the pixel of the locus traced by the pen as the starting point. Since the non-zero area of noise is discrete, labeling does not reach that area. Then, the unlabeled area is erased. Then, a desired extraction region can be obtained as shown in FIG. 41 (b).

FIG. 42 is a block diagram of the tenth area extraction device. This device performs the same processing as the ninth region extraction device
The frame after that is for moving images that can be noise-removed by a simple process just by performing it once. In order to make this possible, the process of calculating the geometric features (e.g. area, center position) of the traced region and the regions of other frames associated with this (49) The processing unit 41 performs the association (50) in the frame. FIG. 43 is a flowchart of this processing, and FIG. 44 is an explanatory diagram thereof. 9th
The same process as the region extraction device of
Eliminate noise as shown in (a). Then, the geometric feature amount of the remaining non-zero area, that is, the extracted area is calculated.

Next, in the second frame, the geometric feature amount is calculated for the non-zero area (including the noise area). Then, the one having the geometric feature amount that is closest to the feature amount of the non-zero area of the first frame is selected, and the others are erased (non-extracted area). After that, the noise region automatically disappears by repeating the same process for the two preceding and following frames.

FIG. 45 is a block diagram of the eleventh area extraction device. This device uses optical (texture) features, whereas the 10th device uses geometric features to identify regions in a frame. Therefore, the processing unit 41
Among them, pixel value composition calculation (5
Do 1). 46 is a flowchart of noise elimination, and FIG. 47 is an explanatory diagram thereof. In either case, the geometrical feature amount is simply replaced with the optical feature amount, and therefore the description is omitted.

[0111]

According to the invention of the third group as described above, there is no need for a photographing facility with a blue background. In addition, it is possible to extract even from images that are not particularly conscious of image composition. The operation is simple because it only requires tracing the necessary parts.

[Invention of Fourth Group] (Outline) The invention of the fourth group provides a display method and device for easily performing processing or changing the display mode for a CG model (including a three-dimensional shape model extracted from a video). It is provided.

[0113]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a three-dimensional shape character display method in which a three-dimensional shape model displayed two-dimensionally on a display is rotated, scaled, moved in parallel by an interactive method, and the result is redisplayed successively. . With the increase in computer speed, it is possible to rotate, scale, and translate the 3D shape model in real time, so that the human can interactively operate the 3D shape model and redisplay the result. Functions are required. Therefore, there is a need for an operation method for rotating, enlarging / reducing, and translating the three-dimensional shape model without disturbing human thinking.

In order to convert a three-dimensional shape model in a three-dimensional space, it is necessary to convert a total of 6 degrees of freedom including rotation 3 degrees of freedom and translation 3 degrees of freedom. When the three-dimensional shape model is displayed two-dimensionally on the display, the movement in the depth direction with respect to the display can be expressed by enlarging or reducing among the above degrees of freedom. Therefore, in this case, a total of 6 degrees of freedom including rotation 3 degrees of freedom, scaling 1 degree of freedom, and parallel movement 2 degrees of freedom are converted. In the conventional three-dimensional model operation, this operation was assigned 6 degrees of freedom x positive and negative to each of the 12 keys of the keyboard. Further, in the operation of a three-dimensional model using a pointing device such as a mouse, the mode is switched so that the pointing device having only two degrees of freedom corresponds to the conversion of six degrees of freedom. As a fusion type of both, there was also a method of operating two degrees of freedom with a pointing device and the remaining four degrees of freedom with a keyboard.

[0115]

In the operating method using the keyboard, since two keys in the positive and negative directions are assigned to each axis, only the conversion in the axial direction can be performed. For example, if vertical and horizontal axes are prepared for parallel movement on a plane, a two-step operation of vertical movement and then horizontal movement (or horizontal movement and then vertical movement) is required for diagonal parallel movement. I need. Further, in the case of rotation, there is a problem that it is very difficult to decompose the assumed conversion into a vector in the axial direction.

Although the operation method using the pointing device can perform the oblique conversion with respect to the axis, it has a problem that mode switching is troublesome and the three degrees of freedom of rotation cannot be operated well. Even if you use the keyboard and pointing device in combination,
It does not mean that the drawbacks of each of them are compensated, only by increasing the problem that operation is difficult due to input from two different devices. Further, regarding the display, there is a problem that it is difficult to know where to rotate the display unless it is actually rotated. The present invention can directly perform conversion in a certain direction, eliminates troublesome operations such as mode switching, and realizes an easy-to-understand operation screen.
It is an object of the present invention to provide a display method and a device capable of performing high-speed and free operation.

[0117]

A method of displaying a three-dimensional shape model according to the present invention is a method of displaying a three-dimensional shape model on a two-dimensional plane, and includes a part or all of the three-dimensional shape model inside. A guide polygon is also displayed, the center of the guide polygon is calculated, and if the point specified by the pointing device is on the periphery of the guide polygon, the calculated center of the guide polygon is used as a reference point of the three-dimensional shape model. When the designated point is outside the guide polygon by enlarging or reducing, and when the designated point is inside the guide polygon, the three-dimensional shape model is rotated with the obtained center of the guide polygon as a reference point. Is characterized in that the three-dimensional shape model is moved. Here, the polygon includes a sphere. The guide polygon is semitransparent, and its color is a color that is easily visible in comparison with the color of the three-dimensional shape model and the background color. Further, the display mode such as movement, enlargement, reduction, rotation, etc. is changed according to the relative positional relationship between the designated point by the pointing device and the guide polygon.

The three-dimensional shape model display device of the present invention is a device for displaying a three-dimensional shape model on a two-dimensional plane, and is a means for calculating a guide polygon including a part or all of the three-dimensional shape model therein. And a means for calculating the center of the guide polygon, a pointing device, a means for comparing a distance l between a point designated by the pointing device and the center of the guide polygon with a radius r of the guide polygon, and when l = r And means for enlarging or reducing the three-dimensional shape model with the center of the guide polygon as a reference point, and rotating the three-dimensional shape model with the center of the guide polygon as a reference point when l <r. Means and means for moving the three-dimensional shape model when 1> r are provided.

FIG. 48 shows a display example of the guide polygon. The three-dimensional shape model is a step-like model, and a sphere enclosing the step model (the latitude line and the meridian line are shown together) is displayed as a guide polygon for guiding recognition or operation. With such a display, the center of enlargement, reduction, or rotation can be recognized at a glance. As shown in FIG. 49, when the point designated by a pointing device such as a mouse is in the guide polygon, rotation is instructed, when it is outside, parallel movement is instructed, and when it is at the periphery, enlargement / reduction is instructed. Then, the amount will be specified by the next operation.

[0120]

BEST MODE FOR CARRYING OUT THE INVENTION The fourth group of inventions will be described in detail below with reference to the drawings showing the embodiments thereof. FIG. 50 is a block diagram of a three-dimensional shape model display device of the present invention. In the figure
A display device 60 includes a pointing device 61 such as a mouse. The shape of the three-dimensional shape model is stored in the shape storage unit 63, the position is stored in the position storage unit 70, and the background image is stored in the background image storage unit 62.

The guide polygon generating unit 64 comprises a color analyzing unit 64a, a color selecting unit 64b, and a shape determining unit 64c, and determines the size and color of the guide polygon required for the subsequent operation. The color analysis unit 64a stores the color information of the background image from the background image storage unit 62,
In addition, the color information of the three-dimensional shape model is fetched and analyzed from the shape storage unit 63, and the color selection unit 64b selects a color that does not interfere with the display of the background and the three-dimensional shape model and is easily visible.
The shape determining unit 64c determines the shape and size of the guide polygon to be displayed.

FIG. 51 is a color selection flowchart, and FIG. 52 is a shape dimension determination flowchart. First, information on the background image and the three-dimensional shape model is respectively fetched from the background image storage unit 62 and the shape storage unit 63, which hue is used for the background image and what percentage is used (S75), and for the three-dimensional shape model. Which hue is used and what percentage is used (S71).
Then, the used hue of the three-dimensional shape is appropriately weighted (S72). The above is the function of the color analysis unit 64a described above, and the following is the function of the color selection unit 64b. That is, the amount of hue in the suburbs is checked from the candidate display colors prepared in advance based on the results of the above analysis (S73). Then, the candidate display color with the smallest hue in the nearest suburb is selected and set as the color of the guide polygon (S74).

Next, the determination of the shape / position will be described.
First, data is taken from the shape storage unit 63 and the position storage unit 70 to calculate the center of gravity of the three-dimensional shape model (S61). Then, this center of gravity is set as the center of the guide polygon (S62). Next, find the distance from this center to each vertex of the 3D shape model.
(S63). Then, let the longest distance be the radius of the guide polygon (S
64) The guide polygon storage unit 65 is caused to store this guide polygon information. When a regular polyhedron that is not a sphere is used as a guide polygon, the same method may be used.

The guide polygons created as described above are displayed on the display device 60 by the display unit 66. The display unit 66 includes a superimposing unit 66a that superimposes the contents read from the guide polygon storage unit 65, the background image storage unit 62, the shape storage unit 63, and the position storage unit 70, and conversion for displaying this on the display device 60. It consists of the display unit 66b.

On the other hand, the input from the pointing device 61 is taken into the interface section 67. Input control unit 67
a controls the pointing device 61, and if the input is linked to the immediately preceding operation like dragging the mouse, it is determined to be a continuation of the conversion performed immediately before. The operation position discriminating unit 67b discriminates whether the input operation start point is outside, inside, or on the boundary of the guide polygon, and operates parallel movement when operated outside, rotation when operated inside, and operates on boundary line. If so, enlargement / reduction is performed. If it is a continuation of the conversion performed immediately before, the same conversion process as the previous conversion is selected.

FIG. 53 is a flow chart showing the processing procedure of the operation position discriminating section 67b. Guide polygon generator 64
The radius determined in step 1 is defined as r (S81), and the distance l between the point designated by the pointing device 61, that is, the operation start point and the center point of the guide polygon is determined (S82). Then, if r = 1, (S83) scaling processing (S86), and if r> l, rotation processing.
(S87) If r <l, parallel movement processing (S85) is performed.

Thus, the operation position information or the operation position determination information is input to the conversion amount determination unit 68, and the parallel movement amount determination unit 68 thereof.
a, the scaling amount determination unit 68b and the rotation amount determination unit 68c respectively determine the translation amount, the scaling amount, and the rotation amount, and these conversion amounts are given to the conversion unit 69, where the conversion corresponding to the conversion amount is performed. Is done. The parallel moving unit 69a, the scaling unit 69b, and the rotating unit 69c perform parallel translation, scaling, and rotation, respectively.

Next, these conversions will be described. First, for the parallel movement, the parallel movement is specified by a method such as positioning the cursor in an area outside the guide polygon (see FIG. 49) and clicking, and then moving (dragging) the cursor in a desired direction. As a result, the three-dimensional shape model and the guide polygon move together. The unit of movement is a pixel. This translation can use various techniques known per se.

Enlargement / reduction will be described below. FIG. 54 is an explanatory view of the principle thereof. First, a point P on the peripheral edge of the guide polygon.
Click at ₁ , drag and then click at position P ₂ according to the magnification to be enlarged or reduced. When the center of the guide polygon is set to 0, it is enlarged or reduced to bar OP ₂ / bar OP ₁ . For the processing of the enlargement / reduction itself, a technique known per se may be appropriately used.

Next, the rotation will be described. Figure 55 is the source
FIG. 56 is a flow chart showing the processing procedure for rotation.
It is a chart. In FIG. 55, D is the display device 60.
2D plane, H is the center of the guide polygon
It is a plane parallel to D passing through. Now point P₁Click on
Instruct to rotate, drag and_PJust rotated
P₂Suppose you click on a point (S91). This P₁, P₂so
Point R projected on the guide polygon₁, R₂Is calculated (S9
2). ∠P₂O'P₁(O 'is the guide port on plane D
The center of Ligon) = α_P(S93). Then ∠R₁OR₂
For this α _rAnd Then R₁O, R₂O (O is
Find the angle formed by the guide polygon center on the plane H)
∠R₁OR₂Α_r(S94). Next, on the reference point O
Reference line L to bar R₁O and bar R₂A straight line perpendicular to O
(S95). And centering on this axis L α_rIs
Rotate (S96). Regarding the processing after determining the rotation amount,
A known figure rotation method may be used. Of such rotation operation
When using a sphere as a guide polygon,
Easy by tracing or referring to meridians and parallels
Can be rotated. The model converted as above
Is input and stored in the position storage unit 70.

FIG. 57 is an overall flow chart of this three-dimensional shape model display device. As described above, first, the guide polygon is determined (S101), then the background, the three-dimensional shape model and the guide polygon are mixedly displayed (S102), and then when the operator designates conversion (S103), the operation area or The movement, enlargement / reduction, and rotation are discriminated (S104), the conversion amount is determined (S106), and the conversion is executed (S107).

[0132]

According to the present invention as described above, the origin (center) of the scaling or rotation can be intuitively recognized. Further, the posture of the three-dimensional shape model can be easily recognized by comparing it with the guide polygon. Moreover, since the color of the guide polygon is automatically determined, there is no fear that the three-dimensional shape model becomes difficult to see. Further, it does not require complicated operations for mode switching for moving, enlarging / reducing, and rotating, and no special device. Further, regarding the rotation, it is possible to input the rotation amount and the direction of 3 degrees of freedom only by inputting the 2 degrees of freedom on the two-dimensional display plane of the display device.
Moreover, the operation is easy as long as it follows the shape of the guide polygon.

[Brief description of drawings]

FIG. 1 is an explanatory diagram of a system of the present invention.

FIG. 2 is a flowchart of a process of a specific object region extraction unit.

FIG. 3 is an explanatory diagram of a structure of a moving image object.

FIG. 4 is a block diagram of an apparatus used to practice the first group of inventions.

FIG. 5 is a flowchart of processing.

FIG. 6 is an explanatory diagram of area designation of a specific object.

FIG. 7 is a flowchart of a three-dimensional shape information addition process.

FIG. 8 is an explanatory diagram of designation of depths of ridge lines and end points.

FIG. 9 is an explanatory diagram of ridge line designation.

FIG. 10 is a block diagram of a three-dimensional shape extraction device.

FIG. 11 is a flowchart of a three-dimensional shape extraction method.

FIG. 12 is a three-dimensional view of a basic shape.

FIG. 13 is an explanatory diagram showing an example of a superimposed display of a basic shape and an image.

FIG. 14 is an explanatory diagram of object area extraction.

FIG. 15 is a flowchart of a process of moving the position of a basic shape.

FIG. 16 is an explanatory diagram of a process of moving the position of the basic shape.

FIG. 17 is a flowchart of a process of rotating a basic shape.

FIG. 18 is an explanatory diagram of a process of rotating a basic shape.

FIG. 19 is a flowchart of a size changing process.

FIG. 20 is an explanatory diagram of a size changing process.

FIG. 21 is an explanatory diagram of mapping.

FIG. 22 is an explanatory diagram of a conventional image synthesizing method.

FIG. 23 is a block diagram of a first area extraction device.

FIG. 24 is a flowchart of region extraction.

FIG. 25 is an explanatory diagram of area extraction.

FIG. 26 is a block diagram of a second area extraction device.

FIG. 27 is a flowchart of region extraction.

FIG. 28 is an explanatory diagram of area extraction.

FIG. 29 is a block diagram of a third to sixth area extracting device.

FIG. 30 is a flowchart of region extraction.

FIG. 31 is an explanatory diagram of area extraction.

FIG. 32 is a block diagram of a third, fourth, seventh and eighth area extracting device.

FIG. 33 is a flowchart of region extraction.

FIG. 34 is an explanatory diagram of area extraction.

FIG. 35 is a block diagram of a third and fourth area extraction device.

FIG. 36 is a flowchart of edge processing.

FIG. 37 is an explanatory diagram of edge processing.

FIG. 38 is an explanatory diagram of edge processing.

FIG. 39 is a block diagram of a tenth area extraction device.

FIG. 40 is a flowchart of noise cancellation.

FIG. 41 is an explanatory diagram of noise cancellation.

FIG. 42 is a block diagram of a tenth area extraction device.

FIG. 43 is a flowchart of noise cancellation.

FIG. 44 is an explanatory diagram of noise cancellation.

FIG. 45 is a block diagram of an eleventh area extraction device.

FIG. 46 is a flowchart of noise cancellation.

FIG. 47 is an explanatory diagram of noise cancellation.

FIG. 48 is a screen diagram showing a display example of a guide polygon.

FIG. 49 is an explanatory diagram of an operation.

FIG. 50 is a block diagram of a three-dimensional shape model display device.

FIG. 51 is a flowchart of color selection of a guide polygon.

FIG. 52 is a flowchart for determining the shape of a guide polygon.

FIG. 53 is a dimensional flowchart for operating position determination.

FIG. 54 is an explanatory diagram of the principle of enlargement / reduction.

FIG. 55 is a diagram illustrating the principle of rotation.

FIG. 56 is a flowchart of rotation.

[Fig. 57] Fig. 57 is an overall block diagram of a display device of a three-dimensional shape model.

[Explanation of symbols]

1 Specific object area extraction unit 2 3D shape information addition section 3 Video CG model generator 4 Composite image generator 5 Image storage 6 Shape / surface attribute information storage 7a, 7b CG model storage 8 Compositing information storage 10 Image display device 12 pointing device 13 CG model creation department

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Kazuki Matsui             1015 Kamiodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture             Within Fujitsu Limited (72) Inventor Shuichi Shiiya             1015 Kamiodanaka, Nakahara-ku, Kawasaki City, Kanagawa Prefecture             Within Fujitsu Limited F-term (reference) 5B050 AA08 AA09 BA07 BA08 BA11                       BA18 DA02 EA19 EA24 EA27                       FA02 FA08                 5C023 AA02 AA10 AA16 BA02 BA13                       DA04 DA08

Claims (2)

[Claims] 1. A method of displaying a three-dimensional shape model on a two-dimensional plane, wherein a guide polygon including a part or all of the three-dimensional shape model therein is also displayed, and a center of the guide polygon is obtained. When the designated point by the pointing device is on the periphery of the guide polygon, the three-dimensional shape model with the obtained center of the guide polygon as a reference point is enlarged or reduced, and the designated point is within the guide polygon. Causes the three-dimensional shape model to rotate with the obtained center of the guide polygon as a reference point, and if the designated point is outside the guide polygon, the three
A method for displaying a three-dimensional shape model, characterized in that the three-dimensional shape model is moved. 2. A device for displaying a three-dimensional shape model on a two-dimensional plane, means for calculating a guide polygon including a part or all of the three-dimensional shape model therein, and means for calculating the center of the guide polygon. A pointing device, a means for comparing a distance l between a point designated by the pointing device and the center of the guide polygon with a radius r of the guide polygon, and when l = r, the center of the guide polygon is used as a reference point. Means for enlarging or reducing the three-dimensional shape model; means for rotating the three-dimensional shape model with the center of the guide polygon as a reference point when l <r; A display device for a three-dimensional shape model, comprising: means for moving the three-dimensional shape model.