• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.158-163
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• 2009

In recent years, there has been increased interest in characterizing and extracting 3D information from 2D images for human tracking and identification. In this paper, we propose a single view-based framework for robust estimation of height and position. In the proposed method, 2D features of target object is back-projected into the 3D scene space where its coordinate system is given by a rectangular marker. Then the position and the height are estimated in the 3D space. In addition, geometric error caused by inaccurate projective mapping is corrected by using geometric constraints provided by the marker. The accuracy and the robustness of our technique are verified on the experimental results of several real video sequences from outdoor environments.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.421-433
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• 2006

This paper proposes a method to insert virtual objects into a real video stream based on feature tracking and camera pose estimation from a set of single-camera video frames. To insert or modify 3D shapes to target video frames, the transformation from the 3D objects to the projection of the objects onto the video frames should be revealed. It is shown that, without a camera calibration process, the 3D reconstruction is possible using multiple images from a single camera under the fixed internal camera parameters. The proposed approach is based on the simplification of the camera matrix of intrinsic parameters and the use of projective geometry. The method is particularly useful for augmented reality applications to insert or modify models to a real video stream. The proposed method is based on a linear parameter estimation approach for the auto-calibration step and it enhances the stability and reduces the execution time. Several experimental results are presented on real-world video streams, demonstrating the usefulness of our method for the augmented reality applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.10-23
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• 2009

The fundamental matrix and key frame selection are one of the most important techniques to recover full 3D reconstruction of objects from turntable sequences. This paper proposes a new algorithm that estimates a robust fundamental matrix for camera calibration from uncalibrated images taken under turn-table motion. Single axis turntable motion can be described in terms of its fixed entities. This provides new algorithms for computing the fundamental matrix. From the projective properties of the conics and fundamental matrix the Euclidean 3D coordinates of a point are obtained from geometric locus of the image points trajectories. Experimental results on real and virtual image sequences demonstrate good object reconstructions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.239-247
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• 2007

The 3D spatial information projects have been processed and utilized in varied fields. However, the research of the 3D digital map for a role of national base map is not enough. The draft maps, which are raw data for generating 2D digital map, shows problems in generating 3D digital map. The objective of this research is to develop 3D digital map editing system for modifying and editing of 3D digital map from 2D vector and raster information such as a draft map, 2D digital map, DEM, aerial photo and so forth. This 3D digital map editing system was designed to include data structure of geometric and attribute object under provision of ISO/TC211 and OGC standard. This system was developed to implement the function of 3D stereo editing based on stereo viewing, 3D view editing based on projective, and 3D spatial operation. Using this system, 3D digital maps were able to be successfully produced from not only existing draft maps but also modified or edited draft maps and then application results were compared and analyzed.