VideoAnnotation : Différence entre versions
De Transport
| Ligne 3 : | Ligne 3 : | ||
merging, splitting, moving positions and adding missing positions (extend trajectories) | merging, splitting, moving positions and adding missing positions (extend trajectories) | ||
| + | Bitbucket repository: https://bitbucket.org/Wendlasida/trafficintelligenceannotationtool/ | ||
| + | ==Tests== | ||
| + | * a test of manual tracking on at least 5 min or 50 vehicles (without starting from the database produced by the automated tracker). The test should be done once with a homography, and a shorter one (on a few tracks (~5) without a homography. | ||
| + | * a test of correcting the automated tracker on a longer period (eg 30 min video, 100s of road users) | ||
| + | In addition to testing the software, this will give us estimates of the time required to clean the data. | ||
| + | * If the previous tests contain few pedestrians (<10), you should extend both so that you track at least 20 pedestrians. | ||
| + | These tests must include saving the data to SQLite, then reloading it and replaying it with the display-trajectories script and plotting them in ipython. | ||
| − | + | ==Resources== | |
* Traffic Intelligence project | * Traffic Intelligence project | ||
* Example of static image annotation http://www.robots.ox.ac.uk/~vgg/software/via/ | * Example of static image annotation http://www.robots.ox.ac.uk/~vgg/software/via/ | ||
Version du 9 juillet 2018 à 15:15
The goal of this project is to develop a graphical tool to annotate video data, in particular road user trajectories and their characteristics (user type). It will help correct and improve the output of the Traffic Intelligence feature-based tracker.
merging, splitting, moving positions and adding missing positions (extend trajectories)
Bitbucket repository: https://bitbucket.org/Wendlasida/trafficintelligenceannotationtool/
Tests
- a test of manual tracking on at least 5 min or 50 vehicles (without starting from the database produced by the automated tracker). The test should be done once with a homography, and a shorter one (on a few tracks (~5) without a homography.
- a test of correcting the automated tracker on a longer period (eg 30 min video, 100s of road users)
In addition to testing the software, this will give us estimates of the time required to clean the data.
- If the previous tests contain few pedestrians (<10), you should extend both so that you track at least 20 pedestrians.
These tests must include saving the data to SQLite, then reloading it and replaying it with the display-trajectories script and plotting them in ipython.
Resources
- Traffic Intelligence project
- Example of static image annotation http://www.robots.ox.ac.uk/~vgg/software/via/
