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场景识别中的视图组合

View combination in scene recognition.

作者信息

Friedman Alinda, Waller David

机构信息

Department of Psychology, University of Alberta, Edmonton, Alberta, Canada.

出版信息

Mem Cognit. 2008 Apr;36(3):467-78. doi: 10.3758/mc.36.3.467.

Abstract

Becoming familiar with an environment requires the ability to integrate spatial information from different views. We provide evidence that view combination, a mechanism believed to underlie the ability to recognize novel views of familiar objects, is also used to recognize coherent, real-world scenes. In two experiments, we trained participants to recognize a real-world scene from two perspectives. When the angular difference between the learned views was relatively small, the participants subsequently recognized novel views from locations between the learned views about as well as they recognized the learned views and better than novel views situated outside of the shortest distance between the learned views. In contrast, with large angles between training views, all the novel views were recognized less well than the trained views. These results extend the view combination approach to scenes and are difficult to reconcile with models proposing that scenes are recognized by transforming them to match only the nearest stored view.

摘要

熟悉一个环境需要整合来自不同视角的空间信息的能力。我们提供的证据表明,视图组合这一被认为是识别熟悉物体新视图能力基础的机制,也被用于识别连贯的现实世界场景。在两项实验中,我们训练参与者从两个视角识别一个现实世界场景。当所学视图之间的角度差异相对较小时,参与者随后能较好地识别所学视图之间位置的新视图,其表现与识别所学视图相当,且优于所学视图最短距离之外的新视图。相比之下,当训练视图之间的角度较大时,所有新视图的识别效果都不如训练视图。这些结果将视图组合方法扩展到了场景,并且难以与那些提出通过将场景进行变换以仅匹配最近存储视图来识别场景的模型相协调。

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