Perceptual grouping strategies and texture segmentation: Strategic connections and selection

被引:2
|
作者
Kon, Maria [1 ,2 ,3 ]
Francis, Gregory [2 ,4 ,5 ]
机构
[1] US Naval Res Lab, Navy Ctr Appl Res Artificial Intelligence, 4555 Overlook Ave SW, Washington, DC 20375 USA
[2] Purdue Univ, Dept Psychol Sci, 703 Third St, W Lafayette, IN 47907 USA
[3] 703 Third St, W Lafayette, IN 47906 USA
[4] Ecole Polytech Fed Lausanne, Lausanne, Switzerland
[5] Univ Aberdeen, Aberdeen, Scotland
基金
美国国家科学基金会;
关键词
Neural network; Grouping; Gestalt; Segmentation; Strategy; Textures; NEURAL DYNAMICS; LAMINAR CIRCUITS; ATTENTION; BINDING; MODEL;
D O I
10.1016/j.visres.2023.108263
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
In a series of articles, Jacob Beck proposed that a variety of texture segmentation phenomena occurs due to emergent features that arise from "links" between elements with appropriate local properties, such as alignment, orientation, and proximity. His findings and ideas guided theoretical and computational models, and some of his demonstrations became textbook knowledge about visual perception. We build on this work in two ways. First, we provide a modern replication of a classic texture segmentation study using a much larger sample size. Overall, the replication agrees with Beck's original findings, although there are some quantitative differences. Second, we show how to apply a quantitative model of visual cortex to Beck's experiment and demonstrate that the model can explain many aspects of Beck's findings. Key to the model's success is cognitive control of connections between individual elements (akin to Beck's "links" between elements) and a selection mechanism that makes it easy to identify how well elements within a region connect and how well different regions are disconnected. Overall, the model supports Beck's claim that local properties can facilitate patterns of connections between stimulus elements and that some connection patterns allow an observer to easily distinguish textures.
引用
收藏
页数:17
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