Semi-automatic photo clustering with distance metric learning

Dinghuang Ji; Meng Wang

doi:10.1117/12.863499

14 July 2010 Semi-automatic photo clustering with distance metric learning

Dinghuang Ji, Meng Wang

Proceedings Volume 7744, Visual Communications and Image Processing 2010; 774409 (2010) https://doi.org/10.1117/12.863499
Event: Visual Communications and Image Processing 2010, 2010, Huangshan, China

Abstract

Photo clustering has been widely explored in many applications such as album management. But automatic clustering can hardly achieve satisfying performance due to the large variety of photos' content. This paper proposes a semi-automatic photo clustering scheme that attempts to improve clustering performance with users' interactions. Users can adjust the results of automatic clustering, and a set of constraints among photos are generated accordingly. A distance metric is then learned with these constraints and we can re-implement clustering with this metric. We conduct experiments on different photo albums, and experimental results have demonstrated that our approach is able to improve automatic photo clustering results, and it is better than pure manual adjustment approach by exploring distance metric learning.

Citation Download Citation

Dinghuang Ji and Meng Wang "Semi-automatic photo clustering with distance metric learning", Proc. SPIE 7744, Visual Communications and Image Processing 2010, 774409 (14 July 2010); https://doi.org/10.1117/12.863499

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