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A 3D Neural Model for Video Analysis
Lucia Maddalena, Alfredo Petrosino
101 - 109
10.3233/978-1-60750-072-8-101
Frontiers in Artificial Intelligence and Applications
Volume 204: Neural Nets WIRN09
Abstract

We propose a 3D self organizing neural model for modeling both the background and the foreground in video, helping in distinguishing between moving and stopped objects in the scene. Our aim is to detect foreground objects in digital image sequences taken from stationary cameras and to distinguish them into moving and stopped objects by a model based approach. We show through experimental results that a good discrimination can be achieved for color video sequences that represent typical situations critical for vehicles stopped in no parking areas.

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