Showing 7 open source projects for "version"

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  • 1
    XIVO

    XIVO

    X Inertial-aided Visual Odometry

    XIVO is an open-source repository for visual-inertial odometry/mapping. It is a simplified version of Corvis [Jones et al.,Tsotsos et al.], designed for pedagogical purposes, and incorporates odometry (relative motion of the sensor platform), local mapping (pose relative to a reference frame of the oldest visible features), and global mapping (pose relative to a global frame, including loop-closure and global re-localization, this feature, present in Corvis, is not yet incorporated in XIVO). ...
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  • 2
    Manifold mesh processing

    Manifold mesh processing

    Mesh and point cloud processing tools

    A suite of tools for processing and analyzing meshes and point clouds. 1) Ensuring that meshes are manifold, ie, "nice" 2) Simple smoothing/noise reduction 3) Bare-bones point cloud to mesh and robust normals for point clouds 4) Mesh simplification 5) Curvature calculation on meshes 6) Local shape descriptors on meshes
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  • 3
    ZPR is a program that produces orthophotos. The method used is to give colors to point-cloud (photo obtained by a digital camera, cloud obtained by a laser scanner) and to project the point-cloud to a requested plane. With this method, the projection pla
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  • 4
    using simple cuboids and gjk algorithm, this general purpose algorithm gives a ready made code to work with swissranger 3D camera.
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  • 5
    Cloud is a point-cloud viewer for Mac OS X. Cloud reads a point-cloud data (e.g. x y z r g b) and renders it by using OpenGL.
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  • 6
    ### mesh reconstruction from point cloud # filters the input data eliminating noise # creates a quad shell - mesh with inside and thickness ### additional info: - GUI using Clan-Lib SDK
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  • 7
    PhotoCloud is a tool to browse and a navigate for datasets composed of (a) a collection of registered images and (b) a 3D model over which images are aligned. The 3D model can be a point-cloud, triangle mesh. PhotoCloud is based on a client/server architecture and it is scalable: very large dataset (both in terms of (a) and (b) can be handled.
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