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Dominant subject recognition by Bayesian learning | IEEE Conference Publication | IEEE Xplore

Dominant subject recognition by Bayesian learning


Abstract:

We tackle the problem of dominant subject recognition (DSR), which aims at identifying the faces of the subject whose faces appear most frequently in a given collection o...Show More

Abstract:

We tackle the problem of dominant subject recognition (DSR), which aims at identifying the faces of the subject whose faces appear most frequently in a given collection of images. We propose a simple algorithm solving the DSR problem in a principled way via Bayesian learning. The proposed algorithm has complexity quadratic in the number of detected faces, and it provides labeling of images along with an accurate estimate of the prediction confidence. The prediction confidence permits using the algorithm in semiautomatic mode when only a subset of images with uncertain labels are corrected manually. We demonstrate on a challenging IJB-B database, that the algorithm significantly reduces the number of images that need to be manually annotated to get the perfect performance of face verification and face identification systems using the face database created by the method.
Date of Conference: 15-18 December 2021
Date Added to IEEE Xplore: 12 January 2022
ISBN Information:
Conference Location: Jodhpur, India

References

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