L. Maddalena, A. Petrosino, The 3dSOBS+ Algorithm for Moving Object Detection, Computer Vision and Image Understanding, DOI: 10.1016/j.cviu.2013.11.006, Vol. 122, pp. 65-73, 2014.
Click here to download the Windows
executable (WinZip compressed) together with the needed OpenCV .dll's.
If you have problems downloading, please contact lucia.maddalena "at" cnr.it; if you use the software, please cite the paper .
3dSOBSplus <SeqName> [Parameters]
o <SeqName>: sequence name (complete path), not including frame numbers. Image sequences consist of .png image frames with consecutive numbers, named in the form <number>.png
o [parameters]: optional, including:
-nini #: Number of first sequence frame to be considered. Default: 1
-nend #: Number of last sequence frame to be considered. Default: 2
-n #: Number of model layers. Default: 5
-F #: Number of initial frames for model initialization. Default: 100
-e #: Segmentation threshold e in Eq. (10). Default: 0.005
-w2d #: Halfwidth of 2D neighborhood for model update in Eq. (4). Default 1
-w1d #: Halfwidth of 1D neighborhood for model update in Eq. (6). Default 1
-lr #: Learning rate g=n in Eqs. (5) and (7). Default 0.05
-Boot #: Read from file the initial background (1) or
compute it through temporal median (0). Default 0
-SmaskMOD: To save the MOD masks. Default: save
-SmodBG: To save the BG models. Default: do not save
Examples of use with generic image sequences:
Provides the above information on usage.
2) 3dSOBSplus C:\Sequenze\BMC2012\111_png\input -nini 1 -nend 450
where sequence 111_png\input, coming from the Background Models Challenge (BMC2012) dataset  , consists of .png image files named:
1.png, …, 1499.png
and stored in directory C:\Sequenze\BMC2012.
This gives the moving object detection mask for the first 450 frames (named bin000001.png, …, bin000450.png) as well as the initial model (named InitialModel.png and stored in the same directory of the input sequence) achieved by temporal median on the first 100 frames, adopted for the neural model initialization.
3) 3dSOBSplus C:\Sequenze\BMC2012\111_png\input\ -ini 1 -end 450 -SmodBG
same as before, but saving in the current directory a representation of the background model for each frame (-SmodBG). For each frame, the representation is built as an image where each pixel is the neural model weight vector that is closest to the corresponding pixel of the frame.
4) 3dSOBSplus C:\Sequenze\BMC2012\111_png\input\ -ini 1 -end 450 -ShowMask 1 -Boot 1
same as before, but showing the foreground masks (-ShowMask 1) and using the already computed initial model InitialModel.png, stored in the same directory of the input sequence (-Boot 1).
 L. Maddalena, A. Petrosino, Stopped Object Detection by Learning Foreground Model in Videos, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2013.2242092, vol.24, no.5, pp.723-735, May 2013.
Last update: November 5, 2015.