= Object Disappearance for Object Discovery =
 * Authors: Julian Mason and Bhaskara Marthi and Ron Parr
 * [[https://users.cs.duke.edu/~parr/iros12.pdf|Paper (.pdf)]]

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##== Citation ==
##{{{
##CHANGEME
##@inproceedings {Quigley2009,
##      title = {ROS: an open-source Robot Operating System},
##      booktitle = {International Conference on Robotics and Automation},
##      series = {Open-Source Software workshop},
##      year = {2009},
##      author = {Morgan Quigley and Ken Conley and Brian Gerkey and Josh Faust and Tully B. Foote and Jeremy Leibs and Rob Wheeler and Andrew Y. Ng}
##}
##}}}
== Code ==
Our code runs against the electric distribution of ROS.  Instructions to build:

 * Download and untar the [[http://download.ros.org/data/mobileobjects/code.tar.gz|code]]
 * Follow [[http://www.ros.org/wiki/electric/Installation|the installation instructions]] for getting the Electric Emys distribution of ROS
 * Add the downloaded code to ROS_PACKAGE_PATH
 * `roscd mobileobjects && rosmake`

It also runs in ROS Fuerte, but has not been extensively tested.

== Running ==
All scripts and launch files are in the `mobileobjects` ROS package.  The launch files and scripts contain documentation on how to set the input data file(s) and other parameters.

 * `launch/dump.launch` launches the MongoDB database instance needed by everything else.
 * `launch/go.launch` launches the initial feature detection (Section V)
 * `scripts/offline_segmenter.py` does the segmentation (Section VI)
 * `bin/feature_extraction` recomputes per-segment features and writes descriptors out (for visual word computation)
 * `scripts/feature_cluster.m` computes visual words (Section VII)
 * `scripts/word_based_tracker.py` does the Dirichlet process data association (Section VIII).
 * `scripts/pipeline.py` runs everything.

== Data ==
The following ROS bags were used as the three datasets in the paper:

 * [[http://download.ros.org/data/mobileobjects/small.bag|Small]]
 * [[http://download.ros.org/data/mobileobjects/medium.bag|Medium]]
 * [[http://download.ros.org/data/mobileobjects/large.bag|Large]]

The attached database contains the state of the large run at the time of submission. That collection is called `large2_seg_update`. The ground-truth segmentations of these objects are in the `data/large2` directory of the released code.

 * [[http://download.ros.org/data/mobileobjects/object-discovery-iros-sub.tar.gz|Archive of the db]]

Due to some nondeterminism in how ROS handles messages, the process of transforming a bagfile into a database (`go.launch`) varies by a few frames. In our experience, this does not change our results by more than 1%. All of our analysis was performed on the same database, posted above.

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## PublicationCategory