WO2009036831A1 - Dispositif et procédé pour aligner un objet en 3d dans une image correspondant à un champ visuel de dispositif de prise de vues - Google Patents

Dispositif et procédé pour aligner un objet en 3d dans une image correspondant à un champ visuel de dispositif de prise de vues Download PDF

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Publication number
WO2009036831A1
WO2009036831A1 PCT/EP2008/005782 EP2008005782W WO2009036831A1 WO 2009036831 A1 WO2009036831 A1 WO 2009036831A1 EP 2008005782 W EP2008005782 W EP 2008005782W WO 2009036831 A1 WO2009036831 A1 WO 2009036831A1
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WIPO (PCT)
Prior art keywords
image
silhouette
intensity
silhouette image
images
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PCT/EP2008/005782
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German (de)
English (en)
Inventor
Peter Eisert
Philipp Fechteler
Jürgen Rurainsky
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Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
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Publication of WO2009036831A1 publication Critical patent/WO2009036831A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30196—Human being; Person
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30221—Sports video; Sports image

Definitions

  • the present invention relates to methods and apparatus for image analysis and synthesis, and more particularly to methods and apparatus for aligning and determining the orientation of a 3D object in an image corresponding to a field of view of a recording apparatus.
  • a virtual fitting of, for example, individualized shoes u.a. used a computer-aided extension of the perception of reality, combining real images or video with virtual 3D objects represented by 3D computer graphics models.
  • a recording device such as a camera
  • a reproduction device for example in the form of a monitor, replaces a real mirror and outputs a horizontally rotated camera image.
  • the monitor is attached in such a way that the person or body parts of it appear at least approximately at the same position where the person would expect to see them if they looked into a real mirror.
  • a background of the images recorded by the recording device is separated from an image foreground and replaced by a synthetic environment.
  • the position and orientation of relevant parts of the body are estimated.
  • computer graphics models eg of garments
  • rendering refers to the generation of a digital image from an image description.
  • the object is achieved by a device according to claim 1, a method according to claim 13 and a computer program according to claim 14.
  • the recognition of the present invention is that alignment of a 3D graphics object in a video image or in a video sequence can be accomplished by using both an image synthesized from the 3D graphics object and a foreground of the recorded image Video sequence silhouettes images are generated. By superimposing the individual silhouette images and determining deviations of the silhouette images from one another, a silhouette of the 3D object can be adapted to a silhouette of the real image at least in a subregion of interest. This is done according to embodiments by means of a gradient-based concept, which uses the so-called optical-flux equation.
  • virtual shoes can be placed over real existing shoes, thus effecting a virtual fitting of the virtual shoes.
  • a person can move freely in front of a recording device.
  • a virtual fitting of other clothing or accessories, jewelry, hairstyles is of course also possible.
  • the present invention provides apparatus for aligning a 3D object in a cradle image corresponding to a field of view of a cradle with means for segmenting the cradle image into foreground and background to obtain a first silhouette image, means for synthesizing a second silhouette image of the 3D object in a starting position and means for estimating alignment parameters for aligning the 3D object with the starting position based on deviations between the first and second silhouette images.
  • the recording device is a camera for two-dimensional recording of video sequences with a predetermined resolution in the horizontal and vertical directions.
  • the SD object in embodiments of the present invention is a 3D object of a shoe, in particular a sports shoe.
  • embodiments of the present invention may serve to facilitate a virtual fitting of shoes, in particular sports shoes.
  • methods for aligning the 3D object according to embodiments are implemented in such a way that they enable the alignment of the 3D object in the recorded image in real time, in order thereby to prevent a movement of a 3D object Person in front of the cradle meet.
  • Real time means the time spent in the "real world".
  • the two silhouette images are each filtered with a low-pass filter to make abrupt silhouette edges into linear ramps with constant To transform intensity gradients.
  • An advantage of the present invention is that movement of body parts of low complexity can be estimated and transmitted to computer graphics models.
  • the low complexity allows a real-time comparison of body movements and 3D object movements.
  • FIG. 1 shows a schematic representation of a virtual mirror as a possible application of exemplary embodiments of the present invention
  • FIG. 2 is a block diagram of an apparatus for aligning a 3D object according to an embodiment of the present invention
  • 3a is a schematic representation of a silhouette image of two legs and shoes according to an embodiment of the present invention.
  • 3b is a schematic representation of a vertical intensity histogram according to an embodiment of the present invention
  • 3c is a schematic representation of a horizontal intensity histogram according to an embodiment of the present invention
  • FIG. 4 is an illustration of a superimposition of a first silhouette image and a second silhouette image in a starting position according to an exemplary embodiment of the present invention
  • FIG. 5 is a diagram for explaining a principle of alignment parameter estimation according to an embodiment of the present invention.
  • FIG. 6 shows a perspective projection in which 3D coordinates of a 3D object point are projected into an image plane
  • FIG. 7a, b show two examples of a shoe rendering with some removed shoe parts according to an embodiment of the present invention.
  • Fig. 1 shows schematically a system 10 for the realization of a virtual mirror, in which embodiments of the present invention may find application.
  • the system 10 comprises a camera 12, a device 14 for processing images recorded with the camera 12. and an output device 16 for outputting a virtual mirror image from an image recorded with the camera 12.
  • the virtual mirror image is computer-aided, for example, with virtual garments, such as shoes, expanded.
  • the camera 12 is directed downwardly for an application of the shoe-fitting system 10 to record the feet of a person standing on a floor 18 in front of the system 10.
  • the legs of the person belonging to the foreground in the real image recorded by the camera 12 are separated in the means 14 for processing from the background of the recorded image and reproduced on the monitor 16 after the recorded image has been horizontally mirrored.
  • the position of the monitor 16 and the viewing direction of the camera 12 are chosen such that an average person on the monitor 16 sees approximately the same as if they were looking at a real mirror mounted in the same position as the monitor 16 ,
  • the bottom 18 in front of the camera 12 is kept green or blue to allow application of so-called chroma keying techniques to facilitate the segmentation of the foreground and background with changing lighting and any colors of clothing.
  • Chroma-keying in film or television technology refers to processes which make it possible to subsequently place objects or persons in front of a background which can contain either a real film recording or a computer graphic.
  • An additional light source below the camera 12 can reduce effects caused by shadows.
  • image processing methods, motion tracking, rendering and computer-aided enhancement of the perception of reality are implemented.
  • the processing device 14 may be a personal computer.
  • the means 14 for processing includes a server that allows control of the system 10 and interfaces with a configuration database.
  • the device 14 comprises, according to exemplary embodiments, a device 20 for aligning a 3D object in an image corresponding to a field of view of the camera 12, which is shown schematically in FIG. 2.
  • the device 20 comprises a device 21 for segmenting the camera image 22 recorded by the camera 12 into a foreground and background in order to obtain a first silhouette image 23. Furthermore, the device 20 comprises a device for synthesizing a second silhouette image 25 of the 3D object in a starting position. The first silhouette image 23 and the second silhouette image 25 form inputs of a device 26 for estimating alignment parameters 27 for aligning the 3D object from the home position based on deviations between the first silhouette image 23 and the second silhouette image 25.
  • the (calibrated) camera 12 continuously records the space in front of the system 10 and transmits the recorded camera images 22, for example with a resolution of 1024 x 768 pixels, to the means 21 for segmentation. All automatic camera controls are switched off in order to avoid unexpected behavior, for example after changing the light. To avoid interference with artificial ambient lighting, the shutter speed of the camera 12 is one with the flicker frequency ambient lighting synchronized. The exposure of the camera 12 is recalculated each time according to one embodiment, and the gain of the camera adjusted accordingly when no one is near the camera 12 to adjust the camera 12 according to changing illumination.
  • An idle state of the system 10 is determined by a change detector that utilizes information about spatial-temporal variations in the video signal 22 provided by the camera 12.
  • a background image is calculated in exemplary embodiments by, for example, averaging ten consecutive video images. This background image is used by the segmentation device 21 to separate the mainly green and blue background of shoes and legs in the foreground of the recorded camera image 22.
  • the means 21 for segmentation is adapted to scale an image resolution of the recorded camera images 22.
  • the image signal processing can take place in a so-called image pyramid.
  • the recorded camera image 22 is filtered and, for example, downscaled four times in succession by a factor of 2, until a resolution of, for example, 64 ⁇ 48 pixels is achieved.
  • Other scaling factors and resolutions are of course also conceivable.
  • the means 21 for segmentation is adapted to separate the foreground and background of the recorded camera image 22 by first of all the background from the foreground for a downscaled image compared to the camera image 22 based on background information and knowledge of Background color and possible shadow fluxes to obtain a low-resolution silhouette image, and thus to detect silhouette edges of the first silhouette image 23 in the resolution of the camera image 22 based on the low-resolution silhouette image and the background information.
  • the separation or segmentation begins, for example, with an image scaled down to 64 ⁇ 48 pixels, in which all the pixel colors of the recorded image are compared with the corresponding pixel colors of the previously calculated background image.
  • RGB red green blue
  • the RGB color space can be schematized in the form of a cube. This color cube is adaptively filled with the green background pixels.
  • the resulting shape of the background pixels in the RGB color cube is extended by cylinder- and cone-like models. After the pixels have been classified, ie, whether they belong to foreground or background, small holes are filled and small areas are removed until only the two legs with the shoes remain. A resulting silhouette image or a segmentation mask is then passed on to higher resolution levels of the image pyramid.
  • edge area means the border area between image foreground and image background.
  • first and second silhouette images can refer to any image pyramid or resolution level.
  • the device 21 comprises a device for determining an area in the first silhouette image 23 at which the 3D object is to be aligned.
  • the means for determining the area is adapted to determine intensity distributions in the horizontal and vertical dimension in the first silhouette image in order to obtain coordinates for the starting position of the 3D object therefrom.
  • horizontal and vertical intensity histograms can be calculated, which can also be used to determine if a person has entered the field of view of the camera 12.
  • FIG. 3a A schematic representation of a silhouette image of two legs and shoes is shown schematically in FIG. 3a.
  • FIG. 3b schematically shows a vertical intensity histogram, which results from the silhouette image according to FIG. 3a.
  • Fig. 3c shows a horizontal intensity histogram resulting from the silhouette image of Fig. 3a.
  • a start of intensity values at ay coordinate y.sub.i can be recognized, y.sub.i thus serving as an indication of the foot position of the feet standing at a vertical height according to this example.
  • Fig. 3c From the horizontal histogram shown in Fig. 3c can be two areas X 1 - x 2 and X 3 - X 4 make up with increased intensity. These two areas correspond to the areas of both legs and feet.
  • the left toe can be determined from the coordinates (X 1 , V 1 ) and the right toe can be determined from the coordinate (x 4 , Y 1 ).
  • the means for determining the area is adapted according to embodiments to the coordinate Y 1 for the Starting position of the 3D object in the vertical direction from an abrupt increase in intensity or decrease in intensity in the vertical direction in a lower portion of the first silhouette image 23, and by a coordinate Xi or X 4 for the initial position of the 3D object in the horizontal direction from an abrupt increase in intensity or intensity decrease in the horizontal direction in the first silhouette image 23.
  • two separate vertical histograms for the areas separated by Xi - X 2 and X 3 - X 4 can be calculated to take into account feet that are not at a common vertical height.
  • Second contour images can now be placed on the output coordinates thus determined by suitably aligning 3D objects (eg, shoe models) that have been synthesized by the device 24. This situation is shown schematically in FIG.
  • FIG. 4 shows a first silhouette image 23 of a shoe with a leg and a second synthesized silhouette image 25 of a 3D object (corresponding to a shoe, for example) in a starting position.
  • the initial position is determined by the start coordinates determined by the histograms and an output orientation (e.g., perpendicular) of the 3D object.
  • the estimation means 26 estimates the alignment parameters for the 3D object by means of a first frame image 23 corresponding to a single frame, which has been derived from a camera image 22 recorded by the camera 12.
  • FIG. Fig. 5 shows a first silhouette image 23 of a leg with shoe and a second silhouette image 25 of a synthesized shoe in a starting position. Movement or alignment parameters for the 3D object of the synthesized shoe are now to be estimated in such a way that a 3D object aligned in accordance with the alignment parameters or the resulting second silhouette image 25 lies above the silhouette of the shoe of the first silhouette image 23 comes. Thereby, the synthetic shoe corresponding to the second silhouette image 25 can be overlaid with the real shoe corresponding to the first silhouette image 23, so that the impression later arises that a person wears the synthesized shoe.
  • the second silhouette image 25 of the 3D object is compared with the first silhouette image 23 of the recorded image.
  • All motion or orientation parameters (R x , R y , R z , t x , t y , t z ) are optimized in order to obtain as perfect a match as possible between the first and second silhouette images.
  • R x , R y and R 2 are rotational angles (eg Euler angles or Euler angles) and t x , t y and t z are components of the displacement or translation vector [t x t y t z ] ⁇ for a 3D object.
  • the device 26 may be provided with texture and color information (possibly additional) to estimate the alignment parameters. That is, the device 26 for estimating the alignment parameters (R x , R y , R z , t x , t y , t z ) is formed in accordance with embodiments to provide texture information from the video image 22 or image signal processing in addition to the silhouette images 23, 25. such as detection of horizontal and / or vertical edges, to use derived image information.
  • the tracking corresponds to the finding of those 3D alignment parameters (R x , R y , R z , t x , t y , t z ) that result in an optimal alignment of the two-dimensional silhouette images 23, 25 (and / or color information ) to lead.
  • a complete search in six-dimensional (or for a pair of shoes in twelve-dimensional space) would be very inefficient at this point. Therefore, the alignment parameters (R x , R y , R z , t x , t y , t z ) are directly calculated according to embodiments using a gradient-based technique.
  • the means 26 is adapted for estimation to filter the first and second silhouette images 23, 25 respectively with a low-pass filter in order to smooth intensity values or gray levels on the silhouette edges of the first and the second silhouette image.
  • this is achieved by a two-dimensional convolution with a separable moving average filter (box filter) with a plurality of coefficients in each dimension.
  • the number of coefficients in the x and y dimensions may be seven, for example, or may be chosen differently depending on the resolution level.
  • This filtering operation transforms the binary silhouette edges into linear ramps with constant intensity gradients.
  • the means 26 for estimating is configured to estimate the alignment parameters 27 based on deviations of intensity values from edge regions of the first and second silhouette images.
  • a system of equations can be set up and solved which is based on a difference (I 2 (x, y) -I x (x, y)) formed from the first and the second silhouette image. and spatial derivatives I x ( ⁇ > y), I y ( ⁇ > y) depend on a constructive overlay formed from the first and second silhouette images and parameters defining the field of view of the capture device. This is done according to embodiments based on the optical flux equation
  • I x ( x > y) has an averaged intensity gradient in the x direction
  • I y (. ⁇ iy) an averaged intensity gradient in the y direction
  • I 2 (x, y) - I 1 (x, y)) an intensity difference between the filtered second silhouette image 25 and the filtered first silhouette image 23
  • d x , d y describe two-dimensional displacement parameters in the x and y directions.
  • the two-dimensional displacement parameters d x , d y are in accordance with Eq. (2) functionally related to the motion parameters (R x , R y , R 2 , t x , t y , t z ).
  • Eq. (2) information about a rigid body motion model and knowledge about parameters of the camera 12.
  • Eq. (2) information for each pixel about the distance z between the camera and the associated object point of the synthesized image 25, which can be determined, for example, efficiently from the z-buffer of the graphics card.
  • a camera model describes a relationship between a 3D virtual world and the camera 12 2D video images and is needed for both rendering and alignment parameter estimation.
  • f x and f y denote the focal length of the camera 12 multiplied by scaling factors in the x and y directions. These scaling factors f x , f y transform the 3D object coordinates [x, y, z] ⁇ into 2D pixel coordinates X and Y. In addition, they allow the use of non-square pixel geometries.
  • the two parameters Xo and Y 0 describe the center of the image and its displacement from the optical axis of the camera 12 due to an unaccurate placement of a CCD (Charge Coupled Device) sensor of the camera 12.
  • the four parameters f x , f y , x o and For example, yo can be obtained from a camera calibration.
  • the averaged intensity gradients I x ( x > y), I y ( ... Iy) can be determined, for example, by a constructive superimposition according to FIG.
  • I x 1 ⁇ y) corresponds to the intensity gradient of the first filtered silhouette image 23 in the x direction and I y 1 (x, y) to the intensity gradient of the first filtered silhouette image 23 in the y direction. decision The same applies to I x 2 (x, y) and I y 2 (x, y) for the second filtered silhouette image 25. I 1 ⁇ y) and I 2 (x, y) respectively correspond to intensities of the first and second filtered silhouette images at the point (x, y). Of course, other pre-scripts to determine the partial intensity derivatives or intensity gradients J x (x, y), I y ( x > y) are also possible.
  • Eq. (1) can be set up for each pixel (x, y) or each inter-pixel position of the silhouette images 23, 25. However, in preferred embodiments of the present invention, it is set up only for those points for which the right-hand part of Eqs. (1) is different from zero.
  • the optical flow condition of Eq. (1) is based on the assumption of a relatively small movement offset between the first silhouette image 23 and the second silhouette image 25.
  • a hierarchical image pyramid approach is followed. In this case, first, a rough estimate of the orientation parameter (R x, R y, R z, t x, t y, t z) based on scaled-down and low-pass filtered silhouette images where the assumption of linearity is valid for a larger image area.
  • 3D computer graphics models of individualized shoes may be provided be rendered at the current image position of the real shoes, so that the person's real shoes in the field of view of the camera 12 are replaced or superimposed by the 3D computer graphics models.
  • the 3D models can be individually configured by, for example, selecting a base model and then choosing between different sole types, materials and colors.
  • individual embroideries e.g. Flags or text to be added.
  • an individual 3D model is assembled. To do this, the geometry, texture, and colors of the 3D models are modified to represent the selected design.
  • Each 3D shoe model consists of various 3D subobjects composed of triangular meshes. These 3D subobjects can be replaced to get different geometries.
  • individualized textures can be selected from a database.
  • the textures can be assigned colors to individualize individual parts of the shoes. In this way, a person can choose between many models and assemble a shoe according to their personal preferences.
  • the 3D object or 3D objects can be used with common SD software tools at the position of real shoes and with orientation determined by the means 26 for estimation.
  • a background is first rendered. This can for example consist of real and / or synthetic videos / animation or individual images. Thereafter, the original video sequence is rendered using the corresponding silhouette image sequence as the alpha channel for the RGBA texture map. The use of intermediate values of the alpha channel at the object edges may improve the embedding of the segmented video sequence in the background.
  • the alpha channel ( ⁇ -channel) is an additional color channel in digital images which, in addition to the color information coded in a color space, stores the transparency or transparency of the individual pixels.
  • the 3D objects are superimposed corresponding to the virtual shoes that cover the original shoes in the segmented video.
  • the legs in the original 2D video should also cover some parts of the synthesized shoes.
  • the Z-buffer of a graphics card can be manipulated so that all overlaps can be correctly detected and the 3D model inserted into the 2D video.
  • Z-buffering is used in computer graphics to detect hidden areas in a 3D computer graphic. Through information in the Z-buffer, the procedure determines pixel by pixel, which elements of a scene must be drawn and which are hidden.
  • Today's graphics cards support Z-Buffering as the standard technique for solving the visibility problem in hardware.
  • the depth information of the generated pixels (the z-coordinate is stored in the so-called Z-buffer.)
  • This buffer usually constructed as a two-dimensional array (with the indices X and Y), contains for each one on the screen visible point of the object a depth value If another object is to be displayed in the same pixel, the rendering algorithm compares the depth values of both objects and assigns the pixel the color value of the object closest to the observer. The depth information of the selected object is then stored in the Z-buffer and replaces the old value.
  • the Z-Buffer allows the graphics card to simulate natural depth perception: a nearby object hides a distant object.
  • the pixel-by-pixel depth values of the z-buffer resulting from the synthesis can be used to efficiently obtain the distance information from object points shown in Eq. (2) needed to be determined.
  • FIGS. 7a and 7b show two examples of a shoe rendering with some removed shoe parts which are later covered by the legs.
  • a camera 12 records a scene with a resolution of 1024 x 768 pixels. A person enters the green area 18 in front of the system 10.
  • embodiments of the present invention provide a concept for real-time 3D motion tracking of objects, particularly shoes, in a virtual mirror environment. From images of a single camera 12, alignment parameters corresponding to the motion of body parts are estimated using low complexity linear optimization methods. Motion tracking is not limited to footwear models but can also be applied to other objects if a corresponding three-dimensional geometry description is available. The motion information or alignment parameters are then used to render customized athletic shoes into the real scene so that a person can observe with the new shoes.
  • the methods according to the invention can be implemented in hardware or software.
  • the implementation may take place on a digital storage medium, in particular a floppy disk, CD or DVD with electronic storage medium.
  • nisch readable control signals that can interact with a programmable computer system so that the appropriate method is executed.
  • the invention thus also consists in a computer program product on a machine-readable medium stored program code for carrying out the method according to the invention, when the computer program product runs on a computer.
  • the present invention is therefore also a computer program with a program code for carrying out the method for aligning, when the computer program runs on a computer and / or microcontroller.

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  • Physics & Mathematics (AREA)
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  • Theoretical Computer Science (AREA)
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Abstract

L'invention concerne un système (20) permettant d'aligner un objet en 3D dans une image correspondant à un champ visuel de dispositif de prise de vues (12), qui comprend un dispositif (21) pour segmenter l'image (22) dans un premier plan et un arrière-plan pour obtenir une première image de silhouette (23), un dispositif (24) pour synthétiser une seconde image de silhouette (25) de l'objet en 3D dans une position de départ, ainsi qu'un dispositif (26) pour évaluer des paramètres d'alignement sur la base d'écarts entre la première et la seconde image de silhouette.
PCT/EP2008/005782 2007-09-14 2008-07-15 Dispositif et procédé pour aligner un objet en 3d dans une image correspondant à un champ visuel de dispositif de prise de vues WO2009036831A1 (fr)

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DE102007043836A DE102007043836B3 (de) 2007-09-14 2007-09-14 Vorrichtung und Verfahren zum Ausrichten eines 3D-Objekts in einem einem Gesichtsfeld einer Aufnahmevorrichtung entsprechenden Bild

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US9489765B2 (en) 2013-11-18 2016-11-08 Nant Holdings Ip, Llc Silhouette-based object and texture alignment, systems and methods
US9728012B2 (en) 2013-11-18 2017-08-08 Nant Holdings Ip, Llc Silhouette-based object and texture alignment, systems and methods
US9940756B2 (en) 2013-11-18 2018-04-10 Nant Holdings Ip, Llc Silhouette-based object and texture alignment, systems and methods

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