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Total Size:
65.4 MB
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F09C12208FB793BBDA4C6068F88CF080F5A4F611
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Added:
Sept. 27, 2025, 4:29 p.m.
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(Last updated: Sept. 27, 2025, 4:34 p.m.)
| File | Size |
|---|---|
| Bullinger S. Image-Based 3D Reconstruction of Dynamic Objects...2019.pdf | 65.4 MB |
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65.4 MB
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2025-09-27
| Uploaded by andryold1 | Size 65.4 MB | Health [ 65 /11 ] | Added 2025-09-27 |
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710.4 MB
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2024-12-02
| Uploaded by FreeCourseWeb | Size 710.4 MB | Health [ 22 /3 ] | Added 2024-12-02 |
NOTE
SOURCE: Bullinger S. Image-Based 3D Reconstruction of Dynamic Objects...2019
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MEDIAINFO
Textbook in PDF format Computing three-dimensional reconstructions of dynamic scenes is one of the fundamental problems in computer vision. For many applications this task can be reduced to the determination of three-dimensional object motion trajectories w.r.t. mainly static environment structures. This approach simplifies the reconstruction problem by constraining projective ambiguities of different scene components. Image-based reconstruction approaches such as Multibody Structure from Motion (MSfM) represent an appealing choice to reconstruct dynamic scenes given suitable conditions like sufficiently textured surfaces and non-degenerated camera trajectories. The underlying assumption of MSfM is that the scene may be represented by a multibody system, i.e., that the scene consists of multiple non-deformable components, which may undergo independent translational and rotational displacements. Existing MSfM approaches use epipolar constraints or motion segmentation to determine component specific feature correspondences to reconstruct independently moving components. Such methods are agnostic to semantics and fail in certain scenarios like stationary or parallel moving objects. It is difficult to identify capabilities and limitations of existing approaches, because of the lack of image-based dynamic object reconstruction baseline algorithms and benchmark datasets
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