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EV-Matching: Bridging Large Visual Data and Electronic Data for Efficient Surveillance
Li, Gang; Yang, Fan; Chen, Guoxing; Zhai, Qiang; Li, Xinfeng; Teng, Jin; Zhu, Junda; Xuan, Dong; Chen, Biao; Zhao, Wei; Lee, K; Liu, L
2017
Conference Name2017 IEEE 37TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2017)
Pages689-698
Publication Place10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
PublisherIEEE COMPUTER SOC
AbstractVisual (V) surveillance systems are extensively deployed and becoming the largest source of big data. On the other hand, electronic (E) data also plays an important role in surveillance and its amount increases explosively with the ubiquity of mobile devices. One of the major problems in surveillance is to determine human objects' identities among different surveillance scenes. Traditional way of processing big V and E datasets separately does not serve the purpose well because V data and E data are imperfect alone for information gathering and retrieval. Matching human objects in the two datasets can merge the good of the two for efficient large-scale surveillance. Yet such matching across two heterogeneous big datasets is challenging. In this paper, we propose an efficient set of parallel algorithms, called EV-Matching, to bridge big E and V data. We match E and V data based on their spatiotemporal correlation. The EV-Matching algorithms are implemented on Apache Spark to further accelerate the whole procedure. We conduct extensive experiments on a large synthetic dataset under different settings. Results demonstrate the feasibility and efficiency of our proposed algorithms.
DOI10.1109/ICDCS.2017.89
URLView the original
Indexed ByCPCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:000412759500063
The Source to ArticleWOS
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Li, Gang,Yang, Fan,Chen, Guoxing,et al. EV-Matching: Bridging Large Visual Data and Electronic Data for Efficient Surveillance[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE COMPUTER SOC,2017:689-698.
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