Moving Object Detection Laboratory, ICAR-CNR
Moving Object Detection Sequences
This page has been created in order to show and make available some manually labelled image sequences used for testing of the
Self-Organizing Background Subtraction (SOBS) algorithm presented in .
Sequence MSA is a home-made indoor sequence manually labeled,
consisting of 528 frames of 320*240 spatial resolution,
acquired at a frequency of 30 fps.
The scene consists of a university hall, where a man comes in,
leaves a bag
on the floor, and then comes out. It represents an
example of easy sequence, in that lighting conditions are
quite stable and
moving objects are well contrasted with the
background (there is no camouflage); however, strong shadows
cast by moving objects can be observed in the entire sequence.
Download the sequence here (27.2MB rar file containing 528 PPM images).
Download the Ground Truth here (txt file containing, for each sequence frame, number of moving objects and their bounding box coordinates).
If you have problems downloading, please contact lucia.maddalena "at" na.icar.cnr.it; if use them, please cite our work .
L. Maddalena, A. Petrosino,
A Self-Organizing Neural System for Background and Foreground Modeling,
in V. Kurkova, R. Neruda, J. Koutnik (eds), “Artificial Neural Networks - ICANN’08”,
Lecture Notes in Computer Science, Vol. 5163, Springer Berlin/Heidelberg, ISBN 978-3-540-87535-2,
DOI 10.1007/978-3-540-87536-9_67, pagg. 652-661, 2008.
Last update: December 6, 2017.