I. Stamos and P. K. Allen. Integration of range and image sensing for photorealistic 3d modeling. In ICRA, 2000.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....image grabbing. The novelty of this paper is in addressing the problem of spending time in range acquisition which has not been accounted for in previous exploration approaches. The number of reconstructions is implicitly considered in view planning and in particular in the best next view problem [15], however, without any optimality claims. In this paper we consider the specific problem of finding a view planning strategy so that an occluded edge becomes visible under the minimal time spent for reconstruction and traveling. Our algorithm can be used as a subroutine by a greedy planner (for ....

I. Stamos and P. K.Allen. Integration of range and image sensing for photorealistic 3d modeling. In Proc. pages 1435--1440, San Fransisco, 2000.

....For rendering they present a viewdependent texture mapping that produces new images by warping and composing multiple views of the scene. When dense range data is available from range finders, it can be combined with the image data to form a detailed image based model [33] or a 3D model [49] of a large scene. In both approaches range data is registered with the image data using line features (edges) In order to compensate the occlusion problem in an e#cient way, Shade et al. 46] introduce layer depth images (LDI) A LDI is a view of the scene from a single camera view point, where ....

I. Stamos and P. K. Allen. Integration of range and image sensing for photorealistic 3d modeling. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 1435--1440, 2000.

....multiple noisy measurements when traversing the same location twice. In the area of computer vision, several researchers have studied the topic of 3D scene reconstruction. Approaches for 3D modeling can be divided into two categories: Approaches that assume knowledge of the pose of the sensors [1, 2, 3, 17, 78], and approaches that do not [35] Our approach uses mobile robots for data acquisition; hence our approach falls into the second category due to the inherent noise in robot odometry (even after pose estimation) The majority of existing systems also require human input in the 3D modeling process. ....

P.K. Allen and Ioannis Stamos. Integration of range and image sensing for photorealistic 3D modeling. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1435-1440, 2000.

....areas like virtual reality, telepresence, access to cultural savings, the problem of constructing 3D models has recently gained serious interest. The approaches described in [2; 3; 5; 19] rely on computer vision techniques and reconstruct 3D models from sequences of images. Allen et al. [1] construct accurate 3D models with stationary range scanners. Their approach also includes techniques for planar approximations in order to simplify the models. However, their technique computes the convex hull of polygons in the same plane and therefore cannot deal with windows or doors. ....

P.K. Allen and Ioannis Stamos. Integration of range and image sensing for photorealistic 3D modeling. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 1435--1440, 2000.

....are correspondence parameters between model components and measurements. In the area of computer vision, 3D scene reconstruction has been studied by several researchers. Approaches for 3D modeling can be divided into two categories: Approaches that assume knowledge of the pose of the sensors (Allen Stamos, 2000; Bajcsy et al. 2000; Becker Bove, 1995; Debevec et al. 1996; Shum et al. 1998) and approaches that do not (Hakim Boulanger, 1997) Our approach uses mobile robots for data acquisition; hence our approach falls into the second category due to the inherent noise in robot odometry (even ....

Allen, P., & Stamos, I. (2000). Integration of range and image sensing for photorealistic 3D modeling (pp. 1435--1440. ).

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I. Stamos and P. K. Allen. Integration of range and image sensing for photorealistic 3d modeling. In ICRA, 2000.

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P. Allen and I. Stamos, "Integration of range and image sensing for photorealistic 3D modeling," in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2000, pp. 1435--1440.

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P.K. Allen and I. Stamos. Integration of range and image sensing for photorealistic 3D modeling. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1435--1440, 2000.

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I. Stamos and P. K.Allen. Integration of range and image sensing for photorealistic 3d modeling. In Proc. of International Conference on Robotics and Automation, pages 1435--1440, San Fransisco, 2000.

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P. Allen and I. Stamos. Integration of range and image sensing for photorealistic 3D modeling. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), pages 1435--1440, 2000.

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P.K. Allen and Ioannis Stamos. Integration of range and image sensing for photorealistic 3D modeling. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1435--1440, 2000. 24

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