Abstract
Interactive retrieval model is a useful solution for the multimedia retrieval applications in case of targets unavailable. The goodness of such model relies on a high coherence between human and machine cognition about the regarded retrieval task. In this paper, we specially perform coherence analysis for interactive face retrieval and explore the influence of metrics to human and machine face recognition in Local Binary Pattern (LBP) feature space. With the collected real user feedback, we discover several new conclusions about unbalanced coherence distribution model and propose an improved correntropy metrics that leads to improved coherence and fast retrieval.
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Fang, Y., Tan, Y., Yu, C. (2014). Coherence Analysis of Metrics in LBP Space for Interactive Face Retrieval. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8325. Springer, Cham. https://doi.org/10.1007/978-3-319-04114-8_2
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DOI: https://doi.org/10.1007/978-3-319-04114-8_2
Publisher Name: Springer, Cham
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