Experiments in Mental Face Retrieval
Experiments in Mental Face Retrieval
复制标题
心理面孔检索实验
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
D. Geman
中科院分区：
文献类型：
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作者：
Yuchun Fang;D. Geman
我们提出了一种从大型图像数据库中检索心理人脸图像的相关反馈系统。这个场景不同于标准的图像检索，因为目标图像只存在于用户的脑海中，用户会响应一系列机器生成的查询，这些查询旨在尽可能快地在脑海中显示这个人。在每次迭代中，用户声明显示的几张脸中哪一张“最接近”他的目标。主要的限制因素是标准的基于强度的特征（用于索引数据库中的图像）与用户头脑中驱动其答案的高级表示之间的“语义差距”。我们探索了一个贝叶斯信息理论框架，用于选择显示哪些图像并对用户的响应进行建模。挑战在于解释心理视觉因素和人类决策变化的来源。我们给出了真实用户的实验来说明和验证所提出的算法。
We propose a relevance feedback system for retrieving a mental face picture from a large image database. This scenario differs from standard image retrieval since the target image exists only in the mind of the user, who responds to a sequence of machine-generated queries designed to display the person in mind as quickly as possible. At each iteration the user declares which of several displayed faces is “closest” to his target. The central limiting factor is the “semantic gap” between the standard intensity-based features which index the images in the database and the higher-level representation in the mind of the user which drives his answers. We explore a Bayesian, information-theoretic framework for choosing which images to display and for modeling the response of the user. The challenge is to account for psycho-visual factors and sources of variability in human decision-making. We present experiments with real users which illustrate and validate the proposed algorithms.