Recognizing and Curating Photo Albums via Event-Specific Image Importance

Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller and Garrison Cottrell

Abstract

Automatic organization of personal photos is a problem with many real world applications, and can be divided into two main tasks: recognizing the event type of the photo collection, and selecting interesting images from the collection. In this paper, we attempt to simultaneously solve both tasks: album-wise event recognition and image-wise importance prediction. We collected an album dataset with both event type labels and image importance labels, refined from an existing CUFED dataset. We propose a hybrid system consisting of three parts: A siamese network-based event-specific image importance prediction, a Convolutional Neural Network (CNN) that recognizes the event type, and a Long Short-Term Memory (LSTM)-based sequence level event recognizer. We propose an iterative updating procedure for event type and image importance score prediction.

Session

Orals - Action Recognition

Files

Paper (PDF)
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DOI

10.5244/C.31.94
https://dx.doi.org/10.5244/C.31.94

Citation

Bibtex

            @inproceedings{BMVC2017_94,
                title={Recognizing and Curating Photo Albums via Event-Specific Image Importance},
                author={Yufei Wang, Zhe Lin, Xiaohui Shen, Radomir Mech, Gavin Miller and Garrison Cottrell},
                year={2017},
                month={September},
                pages={94.1-94.13},
                articleno={94},
                numpages={13},
                booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
                publisher={BMVA Press},
                editor={Tae-Kyun Kim, Stefanos Zafeiriou, Gabriel Brostow and Krystian Mikolajczyk},
                doi={10.5244/C.31.94},
                isbn={1-901725-60-X},
                url={https://dx.doi.org/10.5244/C.31.94}
            }