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VRAR_Readme.txt | ||
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This document, tells you what is contained in this repository and how you are able to use it to |
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- create your one videos (Section B) |
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- render a video (Section A) |
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- create ground-truth-data (Section B) |
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- test a library (Section C) |
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- evaluate the results (Section D) |
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## A Render the Videos ## |
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1. Install and open Blender (Version 2.72a) |
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2. Download and open one of the .blend-Files |
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3. Browse to the "Render"-Tab and set the resolution you want to render |
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4. Set the path ("Output") |
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5. Click on "Render" and wait for the rendering to complete |
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## B Make changes to our videos or create your own videos and create ground truth data ## |
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1. Install and open Blender (Version 2.72a) |
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2. If you want to use your markers, put them in one of the Folders "BART" or "ALVAR" |
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4. Download our plugin for Blender ("Testing" state, not supported by Blenders community) |
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5. Install the Plugin, by copying it to a subdirectory of your plugin-folder. |
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6. Download and open any of our .blend-Files you want to change, or start a new one. |
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7. Make your modifications and click one of the Buttons "BART" or "ALVAR" to reload the markers. |
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- If you want to create new markers use the button "Marker erstellen" |
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- You can make use of the operator "Marker randomisieren" which switches the Texture of the markers 12 times a second. |
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8. Browse to the "Render"-Tab and set the resolution you want to render |
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9. Set the path ("Output") |
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10. Click on "Render" and wait for the rendering to complete |
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11. Insert a path for the ground-truth-data in the text-field below "Positionsdaten ausgeben". |
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NOTE: .txt and .csv-files with the same name as given in this step may be overwritten. |
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12. Create the ground-truth-data by clicking on "Ausgeben". |
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You always get an .csv and a .txt which is more descriptive. |
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## C Test a library ## |
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Find out how you can access the library you want to test and write a connection. If you want to use our scripts for evaluation, you are required to write a csv-file with the following format: |
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frame-number,r1,r2,r3,r4,r5,r6,r7,r8,r9,t1,t2,t3,scale,distance |
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r1 to r9 should give an rotation-matrix and t1 to t3 should give a translation-vector. |
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## D Evaluate the Results ## |
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Regarding to your goal, you need to do your own evaluation of the data given by your library(s) together with the ground-truth-data. |
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If you want to use some of the scripts we created for our work, you should have a look on the following list of scripts: |
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- evaluation/genauigkeit_berechnen.c: This file calculates the detection rate and the accuracy of position-detection |
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- R/rotm.r: Programm to calculate the accuracy of rotation-detection, and paint plots from this data. |
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- R/transl.r: Creates plots from the accuracy of position-detection, calculated in evaluation/genauigkeit_berechnen.c. |
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- R/histogramm_markernummern.r: Creates a histogramm of the detection over the associated marker-ids. |
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- R/main2.r: Converts rotation-accuracy based on rotation-matrices to rotation-accuracy, based on Euler angels. |
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- R/fit.r: Helper, that fits the conversion for one matric. |
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- R/share/hauptdatensaetze_laden.r: A shared script, that loads the necessary files. |
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- R/Bestimmung_Umformungen_Rotm: This folder contains matrices used to adjust rotation-matrices from BART, ALVAR and ARUCO. You may need to do this for your library, if the format of the rotation-matrices contained in r1 to r9 (see Section C) differs from each of the librarys. |
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- R/benchmark.r: This file contains a primitive Benchmark, that compares detection rates. |
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Also available in: Unified diff