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三维物体学习中眼动的特征:模态内与跨模态物体识别的比较

Characteristics of eye movements in 3-D object learning: comparison between within-modal and cross-modal object recognition.

作者信息

Ueda Yoshiyuki, Saiki Jun

机构信息

Kokoro Research Center, Kyoto University, Yoshida Shimoadachi-cho 46, Sakyo, Kyoto 606-8501, Japan.

出版信息

Perception. 2012;41(11):1289-98. doi: 10.1068/p7257.

DOI:10.1068/p7257
PMID:23513616
Abstract

Recent studies have indicated that the object representation acquired during visual learning depends on the encoding modality during the test phase. However, the nature of the differences between within-modal learning (eg visual learning-visual recognition) and cross-modal learning (eg visual learning-haptic recognition) remains unknown. To address this issue, we utilised eye movement data and investigated object learning strategies during the learning phase of a cross-modal object recognition experiment. Observers informed of the test modality studied an unfamiliar visually presented 3-D object. Quantitative analyses showed that recognition performance was consistent regardless of rotation in the cross-modal condition, but was reduced when objects were rotated in the within-modal condition. In addition, eye movements during learning significantly differed between within-modal and cross-modal learning. Fixations were more diffused for cross-modal learning than in within-modal learning. Moreover, over the course of the trial, fixation durations became longer in cross-modal learning than in within-modal learning. These results suggest that the object learning strategies employed during the learning phase differ according to the modality of the test phase, and that this difference leads to different recognition performances.

摘要

最近的研究表明,视觉学习过程中获得的物体表征取决于测试阶段的编码方式。然而,模态内学习(如视觉学习-视觉识别)和跨模态学习(如视觉学习-触觉识别)之间差异的本质仍然未知。为了解决这个问题,我们利用眼动数据,在一个跨模态物体识别实验的学习阶段研究了物体学习策略。被告知测试方式的观察者学习一个以视觉方式呈现的不熟悉的三维物体。定量分析表明,在跨模态条件下,无论物体旋转与否,识别性能都是一致的,但在模态内条件下物体旋转时,识别性能会降低。此外,模态内学习和跨模态学习过程中的眼动存在显著差异。与模态内学习相比,跨模态学习中的注视分布更分散。而且,在试验过程中,跨模态学习中的注视持续时间比模态内学习中的更长。这些结果表明,学习阶段采用的物体学习策略根据测试阶段的方式而有所不同,并且这种差异导致了不同的识别性能。

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