Motion Detection and Clustering Using PCA and NN in Color Image Sequence

Mourad Moussa, Nesrine Bdioui, Ali Douik


This paper presents a motion detection method with the use of the Principal Component Analysis. This method is able to detect and track moving objects in a sequence of images. The tested sequence is segmented within the meaning of movement. In this paper, the concept of extracting significant information from a large number of data is adopted to provide an effective method for tracking moving objects on the video image. The principal components are different in term of getting significant information, the nature of motion (the nature of information) is responsible of this difference, the algorithm in this paper distinguish the motion nature and choose the appropriate components to give a best segmentation.


neural networks; PCA; motion analysis; motion detection; clustering;

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