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ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance

文献类型：期刊论文

作者Li, Da3,4; Zhang, Zhang1,2,3; Yu, Kai5; Huang, Kaiqi6; Tan, Tieniu2,3
刊名IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
出版日期2019-12-01
卷号30期号:12页码:2743-2758
关键词Visualization Surveillance Task analysis Streaming media Computer architecture Pipelines Sparks Intelligent surveillance system big visual data distributed system and parallel computing
ISSN号1045-9219
DOI10.1109/TPDS.2019.2921956
通讯作者Zhang, Zhang(zzhang@nlpr.ia.ac.cn)
英文摘要Intelligent video surveillance (IVS) is always an interesting research topic to utilize visual analysis algorithms for exploring richly structured information from big surveillance data. However, existing IVS systems either struggle to utilize computing resources adequately to improve the efficiency of large-scale video analysis, or present a customized system for specific video analytic functions. It still lacks of a comprehensive computing architecture to enhance efficiency, extensibility and flexibility of IVS system. Moreover, it is also an open problem to study the effect of the combinations of multiple vision modules on the final performance of end applications of IVS system. Motivated by these challenges, we develop an Intelligent Scene Exploration and Evaluation (ISEE) platform based on a heterogeneous CPU-GPU cluster and some distributed computing tools, where Spark Streaming serves as the computing engine for efficient large-scale video processing and Kafka is adopted as a middle-ware message center to decouple different analysis modules flexibly. To validate the efficiency of the ISEE and study the evaluation problem on composable systems, we instantiate the ISEE for an end application on person retrieval with three visual analysis modules, including pedestrian detection with tracking, attribute recognition and re-identification. Extensive experiments are performed on a large-scale surveillance video dataset involving 25 camera scenes, totally 587 hours 720p synchronous videos, where a two-stage question-answering procedure is proposed to measure the performance of execution pipelines composed of multiple visual analysis algorithms based on millions of attribute-based and relationship-based queries. The case study of system-level evaluations may inspire researchers to improve visual analysis algorithms and combining strategies from the view of a scalable and composable system in the future.
WOS关键词FRAMEWORK ; TRACKING
资助项目National Key Research and Development Program of China[2016YFB1001005] ; National Natural Science Foundation of China[61473290]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000498569400010
出版者IEEE COMPUTER SOC
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/29407]  
专题自动化研究所_智能感知与计算研究中心
通讯作者Zhang, Zhang
作者单位1.UCAS, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Inst Automat, CRIPAC, Beijing 100190, Peoples R China
4.UCAS, Sch Artificial Intelligence, Beijing 100049, Peoples R China
5.Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
6.Chinese Acad Sci, Inst Automat, CRISE, Beijing 100090, Peoples R China
推荐引用方式
GB/T 7714		 Li, Da,Zhang, Zhang,Yu, Kai,et al. ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance[J]. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,2019,30(12):2743-2758.
APA Li, Da,Zhang, Zhang,Yu, Kai,Huang, Kaiqi,&Tan, Tieniu.(2019).ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance.IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,30(12),2743-2758.
MLA Li, Da,et al."ISEE: An Intelligent Scene Exploration and Evaluation Platform for Large-Scale Visual Surveillance".IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 30.12(2019):2743-2758.

入库方式： OAI收割

来源：自动化研究所

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