Depth Estimation from Image Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example Based 3D Reconstruction from Single 2D Images
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
3-D Depth Reconstruction from a Single Still Image
International Journal of Computer Vision
Make3D: Learning 3D Scene Structure from a Single Still Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The current of Augmented Reality are data gloves or markers used for interactions between object and background. But, this results in the inconvenience in use and reduced immersiveness. To reinforce immersiveness in AR, added input devices should be removed. To this end, spatial coordinates should be accurately perceived even when a marker has been attached. In this paper, an object expression system was proposed that uses depth-maps for interactions without any additional input devices in order to improve immersiveness. Immersiveness was improved by projecting obtained images on 2D spaces, extracting vanishing lines, calculating the virtual spatial coordinates of the projected images, and varying the sizes of the inserted objects in accordance with the sizes of the areas of virtual coordinates, based on the images projected on the 2D coordinates. By using this system, the use of 3D modelers could be excluded when 3D objects were created; thus, the efficiency of object creation could be improved.