Trajectory based database management for intelligent surveillance system with heterogeneous sensors

Oh, Jung-Min; Moon, Nammee; Hong, Sangjin

doi:10.1007/s11042-015-2725-z

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…Furthermore, authors have also explored the statistics, such as flow maps of individuals attending events, individuals' counts, and share of returning individuals. Oh, et al [27] proposed an intelligent surveillance system in which it gathers heterogeneous sensory information (visual and RFID sensors), creates/updates database information for tracking and identifying objects. The system assigns a global object number to each identified object for maintaining consistent information for the same object.…”

Section: Literature Surveymentioning

confidence: 99%

Real-Time Crowd Monitoring Using Seamless Indoor-Outdoor Localization

Kulshrestha

Saxena

Niyogi

et al. 2020

IEEE Trans. on Mobile Comput.

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Human identification and monitoring are critical in many applications, such as surveillance, evacuation planning. Human identification and monitoring are not an easy task in the case of a large and densely populated crowd. However, none of the existing solutions consider seamless localization, identification, and tracking of the crowd for surveillance in both indoor and outdoor environments with significant accuracy. In this paper, we propose a novel and real-time surveillance system (named, SmartISS) which identifies, tracks and monitors individuals' wireless equipment(s) using their MAC ids. Our trackers/sensing units (PSUs) are the portable entities comprising of Smartphone/Jetson-TK1/PC which are enough to capture users' devices probe requests and locations without users' active cooperation. PSUs upload collected traces on the cloud server periodically where cloud server keeps finding the suspicious person(s). To retrieve the updated information, we propose an algorithm (named, LLTR) to select the optimal number of PSUs for finding the latest location(s) of the suspicious person(s). To validate and to show the usability of SmartISS, we develop a real prototype testbed and evaluate it extensively on a real-world dataset of 117,121 traces collected during the technical festival held at IIT Roorkee, India. SmartISS selects PSUs with an average selection accuracy of 95.3%.

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Section: Literature Surveymentioning

confidence: 99%

Real-Time Crowd Monitoring Using Seamless Indoor-Outdoor Localization

Kulshrestha

Saxena

Niyogi

et al. 2020

IEEE Trans. on Mobile Comput.

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“…Moreover, a new term has been coined to define the application of Cloud Computing (in terms of ubiquity, storage, computation, privacy, scalability, amongst others) to this area: Video Surveillance as a Service [20,29]. For instance, in [27] the authors deal with the problem of integrating heterogeneous sensor information by creating a database scheme able to integrate different types of sensor. However, most of the available solutions rely on wired networks, such as [14,15,21,36].…”

Section: Related Workmentioning

confidence: 99%

Towards a cloud-based automated surveillance system using wireless technologies

et al. 2017

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“…Oh Jung Min et al [23] presented a database management scheme for an intelligent surveillance system utilizing multiple visual sensors and RFID readers. The objects were tracked and identified by multiple visual sensors and RFID readers.…”

Section: Related Workmentioning

confidence: 99%

Guest Editorial: Large-scale Multimedia Data Management: Techniques and Applications

Hung

Takizawa

Chen

2016

Multimed Tools Appl

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Essential to many tasks in relation to multimedia research and development is the availability of a sufficiently large data set and its corresponding ground truth. However, most available data for multimedia research are either too specific, e.g., data for text retrieval; too small, e.g., face figures; nor without ground truth, such as gathering millions of un-preprocessing images from the Web for testing. While it is relatively easy to crawl and store a huge amount of data, the creation of ground truth necessary to systematically train, test, evaluate, and compare the performance of various algorithms and systems remains a challenging issue. For this reason, researchers tend to put (or redirect) efforts into the creation of such corpus individually to carry out research on large-scale data sets. Thus, a promising trend of a united web-scale and distributed multimedia data management is urgently needed, which would benefit the entire multimedia research community. This special issue presents and reports on the construction and analysis of large-scale multimedia data sets and resources, and provides a strong reference for multimedia researchers interested in large-scale multimedia data sets. In particular, the special issue demonstrates the emerging techniques and applications for large-scale multimedia data management.

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Trajectory based database management for intelligent surveillance system with heterogeneous sensors

Cited by 4 publications

References 22 publications

Real-Time Crowd Monitoring Using Seamless Indoor-Outdoor Localization

Real-Time Crowd Monitoring Using Seamless Indoor-Outdoor Localization

Towards a cloud-based automated surveillance system using wireless technologies

Guest Editorial: Large-scale Multimedia Data Management: Techniques and Applications

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