| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 1998: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1997: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Research Abstract |
In this project, several methods for acquiring depth information from images were investigated and an image synthesis method using the information was proposed.
Firstly, two approaches, in which epipolar geometry derived from multi-view images was analyzed to extract depth information, were investigated : one is stereo images and the other is a special case of multi-view system, that is, a monocular image taking a scene in which there exists a mirror. In the approach of stereo vision, disparities on significant edges were calculated by a correlation technology, and a point between two edges in a row line is linearly interpolated its disparity from those of the edges, and the interpolated disparity is corrected so as to be consistent with that obtained by vertical scan. Experimental results showed that this method simply approximate a region with almost homogeneous depth and also separate foreground regions from backgrounds ones. The other approach using a mirror is based on affine trans
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formation. In this method, when four points of an object on desk and their corresponding points reflected on the mirror are given, it is possible to determine 2-D points projected on the image plane of another 3-D object on the desk. This means that CG animation of a real video and a 3-D object in motion can be generated from a special monocular image.
Secondly, 3-D object model reconstructions from images based on 3-D geometry were investigated for image synthesis. A model based volume matching method to extract motion of human being was proposed. It was proved to be possible to identify motion parameters for each pose by matching models with voxel data constructed by four images from different viewpoints.
Thirdly, object tracking by contours to extract depth information were investigated. The object tracking enables to separate foreground regions from background ones in a scene. In this approach, a new region segmentation method based on the Hopfield NN was proposed. Some properties of boundary pixels were embedded in an objective function of the network and the segmentation which minimizes this function was obtained. In order to realize a fast, stable and global region segmentation, pyramid images were used. Experimental results showed that this method is effective for region extraction and motion tracking.
A new image synthesis method without motion incompatibility was also proposed. In this method, when the contours of objects to be superimposed are specified once in the first frame, they are semi-automatically tracked in object image sequence by a hierarchical matching algorithm and an active contour method. In order to synthesize two image sequences without motion incompatibility, position and magnification ratio of an object to be superimposed are determined automatically based on its motion parameters extracted in the process of contour tracking. A new soft-key for blending boundary colors was also proposed to cope with motion blurs. Less
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