Smart surveillance based on video summarization

Thomas, Sinnu Susan; Gupta, Sumana; Subramanian, V.

doi:10.1109/tenconspring.2017.8070003

Cited by 34 publications

(8 citation statements)

References 14 publications

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“…When an emergency is identified, an alert message is sent to a parent's smartphone via Twilio, which is a cloud-based communication platform [111]. Video summarization to reduce the search time from big multimedia data generated by the surveillance system and content image-based retrieval techniques for smart surveillance is detailed in [112]. Aggregated Channel Feature (ACF) extraction and bounding box approach for moving objects are used, and the cost is determined if any critical situation is observed.…”

Section: D: Surveillance For Public Safetymentioning

confidence: 99%

Multimedia Internet of Things: A Comprehensive Survey

et al. 2020

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The immense increase in multimedia-on-demand traffic that refers to audio, video, and images, has drastically shifted the vision of the Internet of Things (IoT) from scalar to Multimedia Internet of Things (M-IoT). IoT devices are constrained in terms of energy, computing, size, and storage memory. Delaysensitive and bandwidth-hungry multimedia applications over constrained IoT networks require revision of IoT architecture for M-IoT. This paper provides a comprehensive survey of M-IoT with an emphasis on architecture, protocols, and applications. This article starts by providing a horizontal overview of the IoT. Then, we discuss the issues considering the characteristics of multimedia and provide a summary of related M-IoT architectures. Various multimedia applications supported by IoT are surveyed, and numerous use cases related to road traffic management, security, industry, and health are illustrated to show how different M-IoT applications are revolutionizing human life. We explore the importance of Quality-of-Experience (QoE) and Quality-of-Service (QoS) for multimedia transmission over IoT. Moreover, we explore the limitations of IoT for multimedia computing and present the relationship between the M-IoT and emerging technologies including event processing, feature extraction, cloud computing, Fog/Edge computing and Software-Defined-Networks (SDNs). We also present the need for better routing and Physical-Medium Access Control (PHY-MAC) protocols for M-IoT. Finally, we present a detailed discussion on the open research issues and several potential research areas related to emerging multimedia communication in IoT. INDEX TERMS Multimedia Internet of Things (M-IoT), multimedia communication, Internet of Multimedia Things (IoMT), multimedia computing, Quality-of-Experience (QoE), Quality-of-Service (QoS), multimedia routing, medium access control (MAC).

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Section: D: Surveillance For Public Safetymentioning

confidence: 99%

Multimedia Internet of Things: A Comprehensive Survey

et al. 2020

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“…The method incorporated is super-oriented optical flow clustering. Thomas et al [5] considers human attention for surveillance video summarisation. Human attention model is used for detecting key events.…”

Section: Surveillance Video Summarisation Frameworkmentioning

confidence: 99%

An aggregated deep convolutional recurrent model for event based surveillance video summarisation: A supervised approach

Sreeja

Kovoor

2021

IET Computer Vision

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Surveillance video summarisation is characterised by extracting video segments containing abnormal events from surveillance video footages. Accurate identification of abnormal events from surveillance footages is of paramount importance in surveillance video summarisation. Accordingly, the proposed framework builds an aggregated convolutional recurrent model that can precisely detect the suspicious events in a surveillance footage, by employing a supervised learning which is found to yield better results compared with unsupervised counterparts. The preliminary stage in the model is a multilayer Convolutional Neural Network for frame-level feature extraction followed by stacked bidirectional Gated Recurrent Unit for sequence-level feature extraction and classification. Since the video clips used for training are not implicit to surveillance, a block-based approach for testing on surveillance videos is proposed. The results evaluated on two custom datasets, Streets and Campus, prove that the proposed model produces remarkable results leveraging the properties of bidirectional GRU with supervised learning. Extensive experimental analysis on selection of optimum architecture is conducted which substantiates the significance of stacked bidirectional GRUs over unidirectional ones. Additionally, qualitative results ensure that summaries produced are concise, representative, complete, diverse and informative. Moreover, comparison of the performance of the proposed model with state of the art certainly proves the superiority of the proposed model.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Secure mobile based video surveillance approach M-IoT [43] Pi camera assisted surveillance system for M-IoT [44] Video with multi-view that is compressed by encoding or decoding scheme for M-IoT [45] Surveillance system for M-IoT based on video-based indoor positioning system [46] Summarization of multi-view videobased on KNN for IoVT [47] Prevention and monitoring of sudden death of infants [48] Summarization of video for smart monitoring system [49] Software-de ned network-based selection scheme for network technique for the real-time data [50] Mechanism of a multi-transport system for M-IoT [51] Tracking applications for IoT based on Quadrotors [52] Automated selection of the size of the transport block for the transmission of video monitoring across the environment [53] Android-based surveillance system for stream and transport protocol [54] Summarization of distributed video using IoVT [55] Vigil based edge computation node for the surveillance of video Planning of path [70] Management of tra c lights based on video and image Guidance scheme for the handling smart city [71] Management of lights in the street [72] Monitoring of Tra c system Automated tra c light based on multimedia [73] Management of smart tra c [74] Management and monitoring of smart tra c for processing the cloud data that is based on mobile multimedia [75] Context-aware and ontology-driven image processing system [76] Monitoring the smart tra c-utilizing video and image [77] Application Framework Year…”

Section: Surveillance Based Security Systemmentioning

confidence: 99%

Current and Potential Applications of IoT in Multimedia Communication System

Jain

Yadav

Alharbi

et al. 2021

Preprint

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Developing wireless technology and the exploitation of automated systems has demanded an innovative method of handling the objects that share multimedia information. The monitoring and automation system has progressed towards the Multimedia Internet of Things (M-IoT) whereas circumstance is entirely transformed to meet the requirements of the fast-moving world. Internet of Things (IoT) engrosses abundant objects and makes those objects think intelligently, which decides on their own by perceiving the situation of the circumstance. The incorporation of IoT into the real-time application facilitates the information exchange and utilizes the information for monitoring as well as prevention of complicated situations. The M-IoT-based conceptual framework and integration of smart objects in real-time applications have enriched the standard of living. M-IoT is widely used in health care, industry, and monitoring event. In this article, the specialized architecture of M-IoT is discussed along with diverse applications. Additionally, the metrics that assess the standard of M-IoT are summarized.

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Smart surveillance based on video summarization

Cited by 34 publications

References 14 publications

Multimedia Internet of Things: A Comprehensive Survey

Multimedia Internet of Things: A Comprehensive Survey

An aggregated deep convolutional recurrent model for event based surveillance video summarisation: A supervised approach

Current and Potential Applications of IoT in Multimedia Communication System

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