Radiant energy – Photocells; circuits and apparatus – Photocell controlled circuit
Reexamination Certificate
2001-04-04
2002-09-24
Le, Que T. (Department: 2878)
Radiant energy
Photocells; circuits and apparatus
Photocell controlled circuit
C356S613000
Reexamination Certificate
active
06455835
ABSTRACT:
FIELD OF THE INVENTION
The teachings of this invention relate generally to computer vision and computer graphics and, more specifically, the teachings of this invention relate to techniques for acquiring silhouettes from an image.
BACKGROUND OF THE INVENTION
A number of different techniques have been developed to compute shapes from silhouettes or contours in the field of computer imaging.
The teachings herein address the problem of acquiring a numerical description of the shape of an object. Given a numerical description of the object's shape it is possible, using well-known computer graphics algorithms, to generate images of the object from different points of view and under different lighting conditions. One important application of such synthetic imagery is in e-commerce, where the seller of an object allows potential customers to inspect a virtual copy of an object interactively using a computer. Numerical representations of objects can be used for other purposes. such as in CAD (computer-aided design) systems as a starting point for the design of new objects.
A class of popular methods for acquiring a numerical representation of an object's shape is known as shape from silhouette, also referred to by similar names such as shape from occluding contour or shape from boundaries. Shape from silhouette algorithms use an image of an object captured by a camera, or any other imaging device. Using the known position of the camera, and the silhouette of the object in the image (i.e. the curve that marks the boundary in the image between the object and the background), an estimate of the numerical shape can be made. A very crude estimate of shape can be obtained from a single image. An improved estimate is obtained using a number of silhouettes from images of the object in different positions relative to the camera.
Many algorithms have been devised to compute a numerical description of the three dimensional shape of an object from silhouettes. One class of algorithms is known as volumetric or space carving, as originally described by Martin and Aggrawal (Worthy N. Martin and J. K Agrawal, “Volumetric Descriptions of Objects from Multiple Views”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, No. 2, March 1983, pp. 150-158.) In this technique a volume of small boxes is numerically defined that completely encloses the object. For each image the boxes are projected onto an image plane. If the projection of a box falls outside of the object silhouette, it is marked as “outside” and is eliminated from a current estimate of the object shape. As each silhouette image is considered more of the boxes are eliminated, or “carved away” from the initial volume. The boxes remaining after all of the silhouette images have been examined is the estimate of the object's shape. A smooth representation of the surface of the object can then be obtained by any well-known isosurface algorithm.
An alternative class of algorithms for extracting shape from silhouettes uses the variation of contour shape in successive images. An example is described by Zheng (Jiang Yu Zheng, “Acquiring 3-D Models from Sequences of Contours”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 2, February 1994, pp. 163-178.) In this method, many silhouette images are obtained as the object is rotated in front of the camera. An estimate of 3D location of points on the object's surface is obtained from the location of silhouettes in the image relative to the projection of the axis of rotation, and the rate of change of these positions with respect to angular change.
There are fundamental limitations on the accuracy of the shape that can be recovered by shape from silhouettes, as discussed by Laurentini (Aldo Laurentini, “How Far 3D Shapes Can Be Understood from 2D Silhouettes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17, No. 2, February 1995, pp. 188-195.). For example, object concavities will not appear in silhouettes, and so will not be captured. To provide the illusion of concavities, and to add color to the model, capture systems generally acquire color images of the object from known camera positions. These color images can be related to the captured geometry by the well-known computer graphics technique known as projective texture mapping. Geometries (generally in the form of triangular meshes) with texture maps can be displayed with hardware and software available on typical personal computers.
A basic operation required by either class of the shape from silhouette algorithms is the accurate extraction of the boundary between the object and the background. This is an example of the classic image segmentation problem from the field of image processing. Systems for extracting shape attempt to simplify the segmentation by designing a suitable backdrop. An example of such a design is illustrated in Jones and Oakely (M. Jones and J. P. Oakley, “Efficient representation of object shape for silhouette intersection”, IEEE Proc.-Vis. Image Signal Process, Vol. 142, No. 6, December 1995, pp. 359-364.) The backdrop for the object is painted a uniform color (in the case of Jones and Oakely “Chromakey Blue”). The silhouette is defined as the boundary of the image regions that are the uniform background color.
An alternative approach uses a large flat diffuse light source in place of the colored backdrop. The silhouette is defined as the boundary of the bright image regions, with the object itself generally appearing dark.
Shape from silhouettes, particularly with the addition of color textures, is a popular technique because it can be implemented inexpensively. The major cost of the system resides in the camera and in a mechanism to control the position of the object, such as a turntable. The implementation with volume carving is particularly attractive for applications because the method guarantees a closed surface.
An alternative and related method for capturing object shape is “shape from shadows”, as described in U.S. Pat. Nos.: 4,792,696 and 4,873,651. These methods are similar to shape from silhouettes, since a sharp shadow is the silhouette projected from a point light source. In both of these patents the camera is placed on the same side of the object as the direction of light incident on the object, and images are taken of the shadows cast by the object. In both of these patents it is assumed that the surface is a height field. That is, the object sits on a reference plane with locations on the plane specified by (x,y) Cartesian coordinates. The shape of the object is given by a third coordinate z that is descriptive of the height of the object surface above the reference plane. With this assumption, the shape of the object surface is inferred from where shadows begin and end, and from knowledge of the light source direction.
U.S. Pat. No.: 4,604,807 employs a shadow that is observed using a camera on the opposite side of the object from the light source. In this patent the shadow is formed by pressing a relatively flat object, e.g., a person's foot, onto a translucent panel. The shadow is observed from the opposite side to obtain a numerical description of the two dimensional area of the foot, and is not used to estimate the three dimensional shape of the foot.
In an article by Leibe et al. (B. Leibe, T. Starner, W. Ribarsky, Z. Wartell, D. Krum, J. Weeks, B. Singletary and L. Godges, “Toward Spontaneous Interaction with the Perceptive Workbench”, IEEE Computer Graphics and Applications, November/December 2000, pp. 54-65.) a system is described that observes shadows cast by objects on a translucent table with a camera located underneath the table. The system can produce only a crude estimate of shape, because the object cannot be repositioned in a calibrated manner.
All of the prior art techniques known to the inventors assume that an accurate silhouette can be extracted from the image. However, if an accurate silhouette cannot be extracted, then the shape of the object will be inaccurate.
The segmentation approac
Bernardini Fausto
Biermann Henning
Rushmeier Holly E.
Savarese Silvio
Taubin Gabriel
International Business Machines - Corporation
Le Que T.
Ohlandt Greeley Ruggiero & Perle LLP
Percello, Esq. Louis J.
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