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• W3047825046 abstract "In this article, we explore the coherence of face perception between human and machine in the scenario of interactive face retrieval. In the part of human perception, we collect user feedback to the stimuli of a target face and groups of displayed candidate face images in a face database with a large number of subjects. In the part of machine vision, we compare the benchmark features and general metrics to measure face similarity. We propose a series of coherence measurements to evaluate the statistic characteristic of human and machine face perception. We discover that despite the unfamiliarity of users to most faces in the database, the coherence between human and machine remains in a stable level across multiple variations in metrics, features, size of databases, and demographics. The simulation experiments with the coherence distributions demonstrate that the embedded information is valuable to speed up interactive retrieval. The comparisons over multiple parameter settings provide feasible instructions in designing the interactive face retrieval system with more consideration of human factors." @default.
• W3047825046 created "2020-08-13" @default.
• W3047825046 creator A5007282525 @default.
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• W3047825046 date "2020-07-31" @default.
• W3047825046 modified "2023-09-24" @default.
• W3047825046 title "On the Perception Analysis of User Feedback for Interactive Face Retrieval" @default.
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• W3047825046 doi "https://doi.org/10.1145/3403964" @default.
• W3047825046 hasPublicationYear "2020" @default.
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