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This paper proposes a novel 3-D modeling technique of an object. The existent 3-D modeling techniques such as stereo vision or factorization recovers 3-D shapes of part of an object observed commonly from multiple orientations. This is followed by registration among recovered partial shapes in order to obtain an entire 3-D model of the object, resulting in some geometrical errors in the linked shape. The proposed technique creates entire shape of an object simultaneously without partial shape registration by the employment of virtual see-through cameras that surround the object and observes its rear part as well as the frontal part. All the surrounding cameras are calibrated initially using the captured images. The frontal side of an object concerned recovers its 3-D shape by the factorization method applied to the image data obtained from the frontal cameras. The recovered frontal shape is virtually projected onto the image planes of the rear cameras. This procedure realizes that all the surrounding cameras observe all the shape of the object, irrespective of frontal or rear. Then the factorization method is applied again to this situation to yield an entire 3-D model of the object. A nonlinear optimization method is employed in the technique to achieve the modeling of higher precision. The proposed technique is applied to the 3-D modeling of a mini basket ball match and their activity is successfully modeled in a 3-D way.
SICE Annual Conference 2010, Proceedings of
Date of Conference: 18-21 Aug. 2010