@inproceedings{18bda003f0a64685814f49513b3887a6,
title = "Utilizing sensor-social cues to localize objects-of-interest in outdoor UGVs",
abstract = "A huge number of outdoor user-generated videos (UGVs) are recorded daily due to the popularity of mobile intelligent devices. Managing these videos is a tough challenge in multimedia field. In this paper, we tackle this problem by performing object-of-interest (OOI) recognition in UGVs to identify semantically important regions. By leveraging geosensor and social data, we propose a novel framework for OOI recognition in outdoor UGVs. Firstly, the OOI acquisition is conducted to obtain an OOI frame set from UGVs. Simultaneously, the classified object set recommendation is performed to obtain a candidate category name set from social networks. Afterward, a spatial pyramid representation is deployed to describe social objects from images and OOIs from UGVs, respectively. Finally, OOIs with their annotated names are labeled in UGVs. Extensive experiments in outdoor UGVs from both Nanjing and Singapore demonstrated the competitiveness of our approach.",
author = "Yingjie Xia and Luming Zhang and Liqiang Nie and Wenjing Geng",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 22nd International Conference on MultiMedia Modeling, MMM 2016 ; Conference date: 04-01-2016 Through 06-01-2016",
year = "2016",
doi = "10.1007/978-3-319-27671-7\_8",
language = "英语",
isbn = "9783319276700",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "88--99",
editor = "Qi Tian and Richang Hong and Xueliang Liu and Nicu Sebe and Benoit Huet and Guo-Jun Qi",
booktitle = "MultiMedia Modeling - 22nd International Conference, MMM 2016, Proceedings",
address = "德国",
}