Advertisement
Published in:
2009 | OriginalPaper | Chapter
3D Neural Model-Based Stopped Object Detection
Authors : Lucia Maddalena, Alfredo Petrosino
Published in: Image Analysis and Processing – ICIAP 2009
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this paper we propose a system that is able to distinguish moving and stopped objects in digital image sequences taken from stationary cameras. Our approach is based on self organization through artificial neural networks to construct a model of the scene background and a model of the scene foreground that can handle scenes containing moving backgrounds or gradual illumination variations, helping in distinguishing between moving and stopped foreground regions, leading to an initial segmentation of scene objects. Experimental results are presented for video sequences that represent typical situations critical for detecting vehicles stopped in no parking areas and compared with those obtained by other existing approaches.