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Testing, validating and applying a general process model (GSDT) of visual search.

测试、验证和应用视觉搜索的通用过程模型（GSDT）。

基本信息

批准号：
401109510
负责人：
Professor Dr. Wolfgang Schwarz
金额：
--
依托单位：
Professur Humanwissenschaftliche Forschungsmethoden
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/401109510?language=en
关键词：
Testing validating applying general process

项目摘要

Schwarz and Miller (2016) presented a comprehensive quantitative process model, called GSDT, to account for all speed- and accuracy-related aspects characterizing performance in the standard paradigm of visual search. GSDT coherently incorporates and integrates four distinct partial processing mechanisms suggested by previous research within a single unified conceptual frame: visual guidance (G), serial (S) object inspection, diffusion (D) modeling of individual object inspections, and a strategic search termination (T) rule. The aim of the proposed project is to explore the validity and wider applicability of GSDT as well as its limits and boundary conditions in four separate Subprojects: (I.) using eye movement data from multiple fixation search to evaluate GSDT's assumptions about seriality and strategic search termination (eye movements are also recorded and analyzed in all Experiments of Subprojects II and III), (II.) using GSDT to coherently account for semantic, categorical, and typicality effects on all aspects of visual search, (III.) using a new, original visual search paradigm to test central GSDT assumptions about visual guidance and target-distractor discriminability, and finally (IV.) applying GSDT to identify exactly which processing mechanisms contribute and combine to the age-related performance decline in visual search. Beyond these novel aspects we will also extend the limited and inconclusive extant evidence regarding the adequacy and validity of GSDT by using, in all four Subprojects, realistic targets and distractors (high-resolution images of real objects). We will also develop and provide (Python-based) software allowing researchers to apply and fit GSDT in a routine manner to single-observer data obtained with the standard search paradigm. Finally, we will quantitatively and systematically compare GSDT to related comprehensive models of visual search such as GS, CGS, parallel diffusion-based models, or TVA.

施瓦茨和米勒（2016）提出了一个全面的定量过程模型，称为GSDT，用于解释标准视觉搜索范式中所有与速度和准确性相关的性能特征。GSDT连贯地结合和整合了四个不同的部分处理机制，在一个单一的统一的概念框架内提出了以前的研究：视觉指导（G），串行（S）对象检查，扩散（D）建模的个别对象检查，和一个战略搜索终止（T）规则。本项目的目的是探讨GSDT的有效性和更广泛的适用性，以及它在四个独立的子项目中的限制和边界条件：（I）使用来自多重注视搜索的眼动数据来评估GSDT关于序列性和策略性搜索终止的假设（在子项目II和III的所有实验中也记录和分析了眼动），（II.）使用GSDT连贯地解释语义，分类和典型性对视觉搜索各个方面的影响，（III.）使用一个新的，原始的视觉搜索范式，以测试中央GSDT假设的视觉指导和目标干扰辨别力，最后（IV.）应用GSDT来准确地识别哪些处理机制对视觉搜索中与年龄相关的性能下降有贡献并联合收割机。除了这些新的方面，我们还将通过在所有四个子项目中使用现实的目标和干扰物（真实的物体的高分辨率图像）来扩展关于GSDT的充分性和有效性的有限的和不确定的现存证据。我们还将开发和提供（基于Python的）软件，使研究人员能够以常规方式将GSDT应用于通过标准搜索范式获得的单观察者数据。最后，我们将定量和系统地比较GSDT与相关的视觉搜索综合模型，如GS，CGS，基于并行扩散的模型或TVA。