Video Surveillance Based on Cloud Storage

Rodríguez-Silva, Daniel A.; Adkinson-Orellana, Lilian; Gonz'lez-Castano, F.J.; Armino-Franco, I.; Gonz'lez-Martinez, D.

doi:10.1109/cloud.2012.44

Cited by 56 publications

(20 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. In contrast to the traditional Video Surveillance [12], NCIVS have integrated two advantaged technology, one is Network Coding Cloud Storage Technology, as is marked by NCDFS in Fig. 1, and the other is Converged Network Video Broadcast and Control System for IPTV, as is marked by NVBCS in Fig.…”

Section: A Architecture Of Systemmentioning

confidence: 99%

Model of Cloud Video Surveillance Based on Network Coding Cloud Storage System

Zhao¹,

Li²,

Li³

et al. 2015

IJFCC

View full text Add to dashboard Cite

Abstract-Video Surveillance is taking an important role in the daily life and social development, the problem of video's storage is more and more serious as the popular and application of the High Definition Video. We designed a model of video surveillance system based on Network Coding Distributed File System, a storage system that applied Self-repair Code Redundancy Theory, whichi is the most advanced theory in the cloud storge area. While the solution of Converged Network Video Broadcast and Control System for IPTV is integrated so that surveillance video content can be delivered seamlessly on the Internet, then surveillance operators can view video on termnails with different operating system anytime and anywhere. The experimental result demonstrate that system greatly saved storge space compared the traditional video surveillance and improved the flexibility of operating.Index Terms-Cloud storge, IPTV, network coding, video surveillance.

show abstract

Section: A Architecture Of Systemmentioning

confidence: 99%

Model of Cloud Video Surveillance Based on Network Coding Cloud Storage System

Zhao¹,

Li²,

Li³

et al. 2015

IJFCC

View full text Add to dashboard Cite

show abstract

“…A cloud-based video surveillance system is proposed in [6] with emphasis on storage. They analyzed the storage requirements of a traditional surveillance system and justified their choice of a cloud-based storage model as an alternative to that of traditional approach.…”

Section: Related Workmentioning

confidence: 99%

“…Such challenges stem from the fact that diverse design decisions need to be made given the abundance of cloud resources and the specific requirements of a surveillance system. Existing work in this direction studies several aspects of cloud-based surveillance system design, for example, dependability characteristics [8], resource allocation [9], video recording [10], cloud storage mechanism [6], and cloud computing suitability for video surveillance [4,11]. However, a holistic approach to develop a multimedia surveillance framework on cloud infrastructure addressing the aforementioned challenges is still missing, which we aim to propose in this paper.…”

Section: Introductionmentioning

confidence: 99%

“…Despite significant benefit these systems provide, they tend to reach their limit in terms of scalability, resource utilization, ubiquitous access, searching, processing, and storage when large-scale surveillance support is required. In order to overcome this situation, a new breed of cloud-based surveillance systems has just started to emerge [4][5][6][7], which utilize the enormous processing capability, storage, and other resources provided by the cloud infrastructure.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Framework for a Cloud-Based Multimedia Surveillance System

Hossain

2014

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

The new generation of multimedia surveillance systems integrates a large number of heterogeneous sensors to collect, process, and analyze multimedia data for identifying events of potential security threats. Some of the major concerns facing these systems are scalability, ubiquitous access to sensory data, event processing overhead, and massive storage requirements-all of which demand novel scalable approach. Cloud computing can provide a powerful and scalable infrastructure for large-scale storage, processing, and dissemination of sensor data. Furthermore, the integration of sensor technology and cloud computing offers new possibilities for efficient development and deployment of sensor-based systems. This paper proposes a framework for a cloud-based multimedia surveillance system and highlights several research and technical issues. A prototype surveillance system is also designed and analyzed in the context of the proposed surveillance framework. The paper finally reports that cloud-based multimedia surveillance system can effectively support the processing overload, storage requirements, ubiquitous access, security, and privacy in large-scale surveillance settings.

show abstract

“…The "RDB-FS" hybrid storage architecture is not easy to expand due to the reduced access efficiency of the RDB when a large amount of GeoVideo data is stored. The robust performance of cloud storage in big data environments, such as its high scalability, high performance, low cost, and ease of deployment, has driven the advent of "video surveillance as a service" [17]. However, at present cloud storage is weak in supporting the spatial information of GeoVideo data and mainly uses a light-weight spatial database engine (SDE) or spatial plug-in to implement limited spatial data management functions, or makes a compromise by carrying out dimension reduction processes [18,19].…”

Section: Introductionmentioning

confidence: 99%

Movement-Oriented Objectified Organization and Retrieval Approach for Heterogeneous GeoVideo Data

Zhu

Zhang

et al. 2018

IJGI

View full text Add to dashboard Cite

Abstract:With the wide deployment of the video sensor network and the rapid development of video spatialization technology, the large volume of complex GeoVideo data necessitates improvements in the application efficiency of the GeoVideo database and GeoVideo surveillance system. Traditional storage management approaches focus on the optimization of access to the GeoVideo stream. However, they suffer from poor management of the diverse movement processes contained within it; for example, they cannot support associative queries or comprehensive analysis of multi-type GeoVideo data in complex geographic environments. This paper takes physical movement process in GeoVideo as a new type of object and carries out an objectified organization of the heterogeneous GeoVideo data around it (including the video stream, spatial references, interpretations of the video data, and the overall scene) in a Not only SQL-Structured Query Language (NoSQL-SQL) hybrid GeoVideo database. This paper systematically explores the hybrid spatiotemporal indexes and multi-modal retrieval methods around movement processes, which enrich the query modes of the GeoVideo data. A prototype implementation and experimental analysis are presented to prove the feasibility and effectiveness of this organization and retrieval approach.

show abstract

Video Surveillance Based on Cloud Storage

Cited by 56 publications

References 2 publications

Model of Cloud Video Surveillance Based on Network Coding Cloud Storage System

Model of Cloud Video Surveillance Based on Network Coding Cloud Storage System

Framework for a Cloud-Based Multimedia Surveillance System

Movement-Oriented Objectified Organization and Retrieval Approach for Heterogeneous GeoVideo Data

Contact Info

Product

Resources

About