Spatio-temporal shape building from image sequences using lateral interaction in accumulative computation

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To be able to understand the motion of non-rigid objects, techniques in image processing and computer vision are essential for motion analysis. Lateral interaction in accumulative computation for extracting non-rigid shapes from an image sequence has recently been presented, as well as its application to segmentation from motion. In this paper, we introduce a modified version of the first multi-layer architecture. This version uses the basic parameters of the LIAC model to spatio-temporally build up to the desired extent the shapes of all moving objects present in a sequence of images. The influences of LIAC model parameters are explained in this paper, and we finally show some examples of the usefulness of the model proposed.

论文关键词:Segmentation from motion,Image analysis,Shape representation,Silhouette recognition,Lateral interaction,Accumulative computation

论文评审过程:Available online 14 December 2002.

论文官网地址:https://doi.org/10.1016/S0031-3203(02)00116-4