@inproceedings{ca28cf3e560b461eb20275b9b99f6a15,
title = "Regional estimation prior network for crowd analyzing",
abstract = "Crowd analysis from images or videos is an important technology for public safety. CNN-based multi-column methods are widely used in this area. Multi-column methods can enhance the ability of exacting various-scale features for the networks, but they may introduce the drawbacks of complicating and functional redundancy. To deal with this problem, we proposed a multi-task and multi-column network. With the support of a regional estimation prior task, components of network may pay more attention to their own target functions respectively. In this way, the functional redundancy can be reduced and the performance of network can be enhanced. Finally, we evaluated our method in public datasets and monitoring videos.",
keywords = "Crowd analysis, Multi-column, Multi-task, Regional estimation, Various-scale features",
author = "Ping He and Meng Ma and Ping Wang",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; 3rd International Conference on Smart Computing and Communications, SmartCom 2018 ; Conference date: 10-12-2018 Through 12-12-2018",
year = "2018",
doi = "10.1007/978-3-030-05755-8_25",
language = "English",
isbn = "9783030057541",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "251--260",
editor = "Meikang Qiu",
booktitle = "Smart Computing and Communication - 3rd International Conference, SmartCom 2018, Proceedings",
address = "Germany",
}