Video surveillance has taken a huge importance in the everyday life, in order to detect, to recognize, to prevent dangerous situations. This work aims to propose two methods able to improve the robustness and speed of the detection of moveable objects or pedestrian using a fixed stereo camera. The first method is an improvement of a real-time adaptive non-parametric threshold with a salt-andpepper noise removal used to detect changes into images. The second method instead proposes to improve the detection of the shadow points in order to affine the extraction of the pedestrians or objects from the scene. Comparison results about accuracy and performance are shown at the end of the paper.

"Auto-adaptive threshold and shadow detection approaches for pedestrians detection,"

MUMOLO, ENZO
2009

Abstract

Video surveillance has taken a huge importance in the everyday life, in order to detect, to recognize, to prevent dangerous situations. This work aims to propose two methods able to improve the robustness and speed of the detection of moveable objects or pedestrian using a fixed stereo camera. The first method is an improvement of a real-time adaptive non-parametric threshold with a salt-andpepper noise removal used to detect changes into images. The second method instead proposes to improve the detection of the shadow points in order to affine the extraction of the pedestrians or objects from the scene. Comparison results about accuracy and performance are shown at the end of the paper.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11368/2844125
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