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Witness detection in multi-instance regression and its application for age estimation

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Abstract

The huge data resource on the Web provides us with an emerging chance to solve the lack of training sample problem that lasting for years in facial age estimation. We show that the web images assisted age estimation can be modeled into a Multiple Instance Regression (MIR) problem. Different from the traditional Multiple Instance Learning (MIL) problem that deals with the bag-level classification task, we model the age estimation problem as an instance-level task. To this end, it is essential to reveal the latent instance labels from all bags. In this paper, we propose a novel algorithm named Witness Detecting Multi-instance Regression (WDMR) that can find all possible positive instances from training bags and use them to train an instance-level regressor. Considering the connection between neighbor relationship and inter-/intra- class differences among instances, we develop a Supervised Citer k-Nearest Neighbor (SC-kNN) graph and a sparse voting strategy to address these problems within a joint learning framework. Experimental results on synthetic and real-world datasets have verified the advantages of our method compared with other state-of-the-art MIL approaches.

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Notes

  1. http://www.csie.ntu.edu.tw/cjlin/libsvm/

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Acknowledgements

This work is supported by the funding of China Scholarship Council (CSC) (No.201706285003), the Provincial Key Laboratory Program of Shaanxi (No. 2013SZS12-K01), and the National Natural Scientific Foundation of China (No.61379104).

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Authors and Affiliations

  1. Institute of Artificial Intelligence & Robotics, Xi’an Jiaotong University, Shaanxi, 710049, China

    Jianyi Liu, Rui Qiao & Yueying Li

  2. Department of Computer Science, University of Georgia, Athens, GA, 30602, USA

    Sheng Li

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  1. Jianyi Liu
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  2. Rui Qiao
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  3. Yueying Li
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  4. Sheng Li
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Correspondence to Jianyi Liu.

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Liu, J., Qiao, R., Li, Y. et al. Witness detection in multi-instance regression and its application for age estimation. Multimed Tools Appl 78, 33703–33722 (2019). https://doi.org/10.1007/s11042-019-08203-x

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