[1]杜潘飞,王志辉,李雄伟,等.异常行为检测数据集快速构建方法[J].计算机技术与发展,2021,31(09):155-160.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 026]
　DU Pan-fei,WANG Zhi-hui,LI Xiong-wei,et al.Fast Construction Strategy of Abnormal Action Detection Dataset[J].,2021,31(09):155-160.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 026]
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异常行为检测数据集快速构建方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年09期
页码:
155-160
栏目:
应用前沿与综合
出版日期:
2021-09-10

文章信息/Info

Title:
Fast Construction Strategy of Abnormal Action Detection Dataset
文章编号:
1673-629X(2021)09-0155-06
作者:
杜潘飞1 ; 王志辉2 ; 李雄伟1 ; 朱永旺2
1. 陆军工程大学 石家庄校区,河北 石家庄 050003;
2. 河北建设投资集团有限责任公司,河北 石家庄 050001
Author(s):
DU Pan-fei1 ; WANG Zhi-hui2 ; LI Xiong-wei1 ; ZHU Yong-wang2
1. Shijiazhuang Campus,The Army Engineering University of PLA,Shijiazhuang 050003,China;
2. Hebei Construction & Investment Group Co. ,Ltd. ,Shijiazhuang 050001,China
关键词:
数据集构建; 行为识别; 目标检测; 半自动构建方法; 异常行为
Keywords:
dataset construction; action recognition; object detection; semi-automatic construction method; abnormal action
分类号:
TP391. 4
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 09. 026
摘要:
文中提出一种快速构建异常行为检测数据集方法,该方法以一种半自动的方式完成数据集的构建,有助于减少构建过程中人工操作的工作量。 首先以网络爬虫的方式自动地从互联网上搜索并下载包含指定动作的视频,之后以当前SOTA( state-of-the-art) 的目标检测模型作为人物空间位置检测器,最后以人工标注和行为检测模型相结合的迭代方式完成人物行为的标注,其中需要手工完成的主要包括对下载的视频的挑选、人物边框核对以及一部分的行为标注,手工部分的工作量仅占整个任务的工作量的 15% 左右。 实验表明,由该方法所构建的数据集可以作为异常行为检测模型的训练集使用,验证了该方法的有效性。 通过该方法可以快速地构建一个大尺度、高质量的行为检测数据集,将有助于推动异常行为检测研究的深入开展。
Abstract:
We propose a fast strategy to build abnormal action detection dataset. This strategy completes the construct-ion of dataset in a semi-automatic way,which significantly reduces the workloads of manual operation in the construction pipeline. This method searches and downloads videos containing specified actions automatically from the Internet in the form of web crawler. The object detection model with the state-of-the-art performance is used as the person spatial detector. Finally, the human action annotations are complete diteratively by combining manual annotation and action detection model. What needs to be done manually is the selection? of down loaded video,the check of person bounding boxes and a part of action annotations. In the experiment section,it demonstrates that the dataset constructed by this method is effective and can be used as the training set of abnormal action detection model. Furthermore,it shows that this method can quickly build a large-scale and high-quality action detection dataset,which will accelerate the development of research and application of abnormal action detection.

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更新日期/Last Update: 2021-09-10