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Quantitative description of the laws of perceptual grouping by means of the principle of representational minimum description length

机译:通过代表性最小描述长度的原理对感知分组定律的定量描述

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This paper discusses the problem of quantitatively describing the laws of perceptive grouping developed in Gestalt psychology and their use in computer vision. For a unified description of the Gestalt laws, the principle of representational minimum description length is proposed. Psychophysical experiments have been carried out in which it is established that the probability that a person will distinguish a stimulus depends predominantly on the information content of the stimulus, expressed in the reduction of the description length (in the framework of the given representation) of the elements of the visual scene when the stimulus is described separately from the field elements. A computer model is constructed and experimentally checked that groups the structural elements of the image, based on an informational criterion and a representation that embodies some of the Gestalt laws. (C) 2008 Optical Society of America.
机译:本文讨论了定量描述格式塔心理学中感知分组法则及其在计算机视觉中的应用的问题。为了对格式塔定律进行统一描述,提出了最小描述长度的表示原则。已经进行了心理物理实验,其中确定了一个人区分刺激的概率主要取决于刺激的信息内容,以减少描述长度(在给定表示的框架内)表示。当刺激与场要素分开描述时,视觉场景的要素。基于信息标准和体现格式塔定律的表示法,构建并通过实验检查了计算机模型,该模型对图像的结构元素进行了分组。 (C)2008年美国眼镜学会。

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