## Moving Object Detection Laboratory, ICAR-CNR

# Moving Object Detection Software: SOBS

This page has been created in order to distribute a prototype software implementing the
Self-Organizing Background Subtraction (SOBS) algorithm presented in
L. Maddalena, A. Petrosino,
*A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications*,
**IEEE Transactions on Image Processing**, DOI:
10.1109/TIP.2008.924285, Vol. 17, no. 7, pagg. 1168-1177, July 2008

Click here to download the Windows executable (WinRar compressed).
If you have problems downloading, please contact lucia.maddalena "at" cnr.it;
if you use the software, please cite the above mentioned paper.
**Usage:**

SOBS <SeqName>
<#FirstFrame> <#LastFrame> [Parameters]

where

o <SeqName>: sequence name
(complete path), not including frame numbers. Image sequences consist of binary PPM image frames with consecutive
numbers, named in the following form

<SeqName>.<number>.ppm

The number of digits for
<number> must be the same for all sequence frames (e.g. a sequence with
120 frames must be numbered from 1001 to 1120, and not from 1 to 120)

o <#FirstFrame>, <#LastFrame>: number of first and last
sequence frame to be considered.

o [parameters]: optional, including:

-n #: (square root of) number of weight vectors for each pixel. Default 3

-K #: Number of initial frames for calibration. Default 200

-e1 #: Distance threshold e_{1} for calibration phase (eqn. (2)). Default 0.1

-e2 #: Distance threshold e_{2} for online phase (eqn. (2)). Default 0.03

-c1 #: Learning rate c_{1} for calibration phase (eqn. (4)).
Default 1.0

-c2 #: Learning rate c_{2} for online phase (eqn. (4)). Default
0.05

-g #: Value for g in
eqn. (5). Default 0.7

-b #: Value for b in
eqn. (5). Default 1.0

-tS #: Value for t_{S} in eqn. (5). Default 0.1

-tH #: Value for t_{H} in eqn. (5). Default 10.0

-s: To apply shadow removal.
Default: no shadow removal

-m: To save background model
images. Default: do not save

-l: To save just last
detection mask. Default: save all

**Example of use:**

SOBS c:/Sequences/WavingTrees/WavingTrees 1000 1247 -n
3 -e1 0.1 -e2 0.03 -K 200 -c1 1.0 -c2 0.05 –l

where
sequence *WavingTrees*, coming
from sequences adopted in K. Toyama, J. Krumm, B. Brumitt, and B. Meyers,
“Wallflower: principles and practice of background maintenance,” in *Proc.
7th IEEE Conf. Computer Vision*, 1999, vol. 1, pp. 255–261, has been saved
in binary PPM image files named:

WavingTrees.1000.ppm,
…, WavingTrees.1247.ppm

and
stored in directory c:/Sequences/WavingTrees.

*Last update: March 5, 2009.*