@inproceedings{df48d06c429d4f7e85ce6a28afa5fb93,
title = "Dynamic region selection in video based on spatio-temporal multiple instance learning",
abstract = "The selection of dynamic region in video plays an important role in many subsequent vision-based applications, especially in scene classification with different weather conditions. In this paper, we extract five local features from pixel blocks of each frame in a video, and propose an approach to dynamic region selection based on a presented description of spatio-temporal multiple instances. The effectiveness of our method is shown using experiments on videos under different weather environments.",
keywords = "Dynamic region, K-means, Multi-instance, Spatio-temporal feature",
author = "Wang, \{Xiao Zheng\} and Zhao, \{Xu Dong\} and Peng Liu and Tang, \{Xiang Long\}",
note = "Publisher Copyright: {\textcopyright} 23rd International Conference on Computer Graphics and Vision, GraphiCon 2013 - Conference Proceedings. All rights reserved.; 23rd International Conference on Computer Graphics and Vision, GraphiCon 2013 ; Conference date: 16-09-2013 Through 20-09-2013",
year = "2020",
language = "英语",
series = "23rd International Conference on Computer Graphics and Vision, GraphiCon 2013 - Conference Proceedings",
publisher = "GraphiCon Scientific Society",
pages = "103--105",
booktitle = "23rd International Conference on Computer Graphics and Vision, GraphiCon 2013 - Conference Proceedings",
}