motion detection based on background subtraction approaches require a background model generation before extracting the moving objects. This extraction consists to subtract the static scene from the current image. The...
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ISBN:
(纸本)9781509004782
motion detection based on background subtraction approaches require a background model generation before extracting the moving objects. This extraction consists to subtract the static scene from the current image. The result of subtraction will be segmented in order to represent the moving object by a binary image using a threshold. In this paper a new background subtraction approach is presented. Firstly, each gray-level image of the sequence will be decomposed on two components, structure and texture/noise by applying the Osher and Vese algorithm. The structure component of each image will be taken to generate the background model. The background model development uses a threshold in order to decide if a pixel belongs to the background or to the foreground. The absolute difference is used to subtracting the background before compute the binary image of the moving objects using a proposed threshold selection operation. The experimental results demonstrate that our approach is effective and accurate moving objects detection comparing with the results of two existing methods.
作者：
I. BellamineH. TairiLIIAN
Department of mathematics and computer Mohamed Ben Abdellah University
Space-Time Interest Points (STIP) are among all the interesting features which can be extracted from videos;they are simple, robust and they allow a good characterization of a set of regions of interest corresponding ...
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ISBN:
(纸本)9781479907915
Space-Time Interest Points (STIP) are among all the interesting features which can be extracted from videos;they are simple, robust and they allow a good characterization of a set of regions of interest corresponding to moving objects in a three-dimensional observed scene. In this paper, we show how the resulting features often reflect interesting events that can be used for a compact representation of video data as well as for tracking. For a good detection of moving objects, we propose to apply the algorithm of the detection of spatiotemporal interest points on both components of the decomposition which is based on a partial differential equation (PDE): a geometric structure component and a texture component. Proposed results are obtained from very different types of videos, namely sport videos and animation movies.
motion detection based on background subtraction approaches require a background model generation before extracting the moving objects. This extraction consists to subtract the static scene from the current image. The...
详细信息
ISBN:
(纸本)9781509004799
motion detection based on background subtraction approaches require a background model generation before extracting the moving objects. This extraction consists to subtract the static scene from the current image. The result of subtraction will be segmented in order to represent the moving object by a binary image using a threshold. In this paper a new background subtraction approach is presented. Firstly, each gray-level image of the sequence will be decomposed on two components, structure and texture/noise by applying the Osher and Vese algorithm. The structure component of each image will be taken to generate the background model. The background model development uses a threshold in order to decide if a pixel belongs to the background or to the foreground. The absolute difference is used to subtracting the background before compute the binary image of the moving objects using a proposed threshold selection operation. The experimental results demonstrate that our approach is effective and accurate moving objects detection comparing with the results of two existing methods.
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