The detection of moving people is an important task for video surveillance systems. This paper presents a motion segmentation algorithm for detecting people moving in indoor environments. The proposed algorithm works with mobile cameras and it is composed of two main parts. In the first part, a frame-by-frame procedure is applied to compute the difference image, and a neural network is used to classify whether the resulting image represents a static scene or a scene containing mobile objects. The second part tries to reduce the detection errors in terms of both false or missed alarms. A finite state automaton has been designed to give a robust classification and to reduce the number of false or missed blobs. Finally, a bounding ellipse is computed for each detected blob in order to isolate moving people. (c) 2005 Elsevier B.V. All rights reserved.

Detecting moving people in video streams

FORESTI, Gian Luca;MICHELONI, Christian;PICIARELLI, Claudio
2005-01-01

Abstract

The detection of moving people is an important task for video surveillance systems. This paper presents a motion segmentation algorithm for detecting people moving in indoor environments. The proposed algorithm works with mobile cameras and it is composed of two main parts. In the first part, a frame-by-frame procedure is applied to compute the difference image, and a neural network is used to classify whether the resulting image represents a static scene or a scene containing mobile objects. The second part tries to reduce the detection errors in terms of both false or missed alarms. A finite state automaton has been designed to give a robust classification and to reduce the number of false or missed blobs. Finally, a bounding ellipse is computed for each detected blob in order to isolate moving people. (c) 2005 Elsevier B.V. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/879932
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