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Algorithm: Tracking 3D Shapes in Noisy Point Clouds with Random Hypersurface Models

Description:
Example estimation of a cylinder
Paper: Florian Faion, Marcus Baum, and Uwe D. Hanebeck. Tracking 3d shapes in noisy point clouds with random hypersurface models. In Proceedings of the 15th International Conference on Information Fusion (Fusion 2012). Singapore, July 2012.
Tags: Tracking Random Hypersurface Model RHM Bayesian
Usage: Algorithm is public.
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Florian Faion
07/10/2012 4:24 p.m. (version #1)

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Using this algorithm in your local MATLAB environment is easy: Click here for instructions!

Usage Instructions for CloudRunner Client

  1. Download the CloudRunner Client by clicking here and place the downloaded file in your MATLAB working directory.

  2. Inside MATLAB, initialize the CloudRunner Client by calling CloudRunner:
    >> CloudRunner

    A login dialog will prompt for your CloudRunner mail address and password. For a start, you can leave the dialog empty and just click "Connect".

    Alternatively, you can provide the login credentials (or empty strings to skip login) as a parameter and hence skip the login dialog. This is useful when using CloudRunner in non-interactive scripts.
    >> CloudRunner('mail@example.com', 'password')

  3. Select this algorithm by its URL. Selecting an algorithm creates the lambda function that proxies calls to the algorithm to the server for execution:
    >> CloudRunnerSelect('http://www.cloudrunner.eu/algorithm/66/tracking-3d-shapes-in-noisy-point-clouds-with-random-hypersurface-models/version/1/')

    For the sake of convenience, you can also use the algorithm ID instead of its URL for public algorithms.

  4. Call functions from the algorithm like any regular local function.

Note: You can find further information on the help page.

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