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 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.展开更多
基金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.
文摘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.
