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PhotoPrev: Unifying Context and Content Cues to Enhance Personal Photo Revisitation

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Abstract

Personal photo revisitation on smart phones is a common yet uneasy task for users due to the large volume of photos taken in daily life. Inspired by the human memory and its natural recall characteristics, we build a personal photo revisitation tool, PhotoPrev, to facilitate users to revisit previous photos through associated memory cues. To mimic users’ episodic memory recall, we present a way to automatically generate an abundance of related contextual metadata (e.g., weather, temperature) and organize them as context lattices for each photo in a life cycle. Meanwhile, photo content (e.g., object, text) is extracted and managed in a weighted term list, which corresponds to semantic memory. A threshold algorithm based photo revisitation framework for context- and content-based keyword search on a personal photo collection, together with a user feedback mechanism, is also given. We evaluate the scalability on a large synthetic dataset by crawling users’ photos from Flickr, and a 12-week user study demonstrates the feasibility and effectiveness of our photo revisitation strategies.

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Correspondence to Li Jin.

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The work was supported by the National Natural Science Foundation of China under Grant Nos. 61373022, 61073004, and the National Basic Research 973 Program of China under Grant No. 2011CB302203-2.

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Jin, L., Liu, GL., Zhao, L. et al. PhotoPrev: Unifying Context and Content Cues to Enhance Personal Photo Revisitation. J. Comput. Sci. Technol. 30, 453–466 (2015). https://doi.org/10.1007/s11390-015-1536-z

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  • DOI: https://doi.org/10.1007/s11390-015-1536-z

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