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Colloquia

Alignment of Continuous Video onto 3D Point Clouds and Automatic Registration and Visualization of Occluded Targets Using Ladar Data

Stephen Hsu
Senior Member Technical Staff
Sarnoff Corporation
Princeton, NJ

Wednesday, March 09, 2005
DCC 330 - 4:00 p.m. to 5:00 p.m.
Refreshments at 3:30 p.m.

Alignment of Continuous Video onto 3D Point Clouds
W. Zhao, D. Nister, S. Hsu

We propose a general framework for aligning continuous (oblique) video onto 3D sensor data. We align a point cloud computed from the video onto the point cloud directly obtained from a 3D sensor. This is in contrast to existing techniques where the 2D images are aligned to a 3D model derived from the 3D sensor data. Using point clouds enables the alignment for scenes full of objects that are difficult to model, for example, trees. To compute 3D point clouds from video, motion stereo is used along with a state-of-the-art algorithm for camera pose estimation. Our experiments with real data demonstrate the advantages of the proposed registration algorithm for texturing models in large-scale semi-urban environments.
The capability to align video before a 3D model is built from the 3D sensor data opens up new possibilities for 3D modeling. We introduce a novel modeling-through-registration approach that fuses 3D information from both the 3D sensor and the video. Initial experiments with real data illustrate the potential of the proposed approach.

Automatic R egistration and Visualization of Occluded Targets Using Ladar Data
S. Hsu, S. Samarasekera, R. Kumar

High-resolution 3D imaging ladar systems can penetrate foliage and camouflage to sample fragments of concealed surfaces of interest. Samples collected while the ladar moves can be integrated into a coherent object shape, provided that sensor poses are known. We detail a system for automatic data-driven registration of ladar frames, consisting of a coarse search stage, a pairwise fine registration stage using an iterated closest points algorithm, and a multi-view registration strategy. We evaluate this approach using simulated and field-collected ladar imagery of foliage-occluded objects. Even after alignment and aggregation, it is often difficult for human observers to find, assess, and recognize objects from a point cloud display. We survey and demonstrate basic display manipulations, surface fitting techniques, and clutter suppression to enhance visual exploitation of 3D imaging ladar data.

Host: Chuck Stewart, x6731

Last updated: March 3, 2005



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