Low-Complexity Big Video Data Recording Algorithms for Urban Surveillance Systems
نویسندگان
چکیده
منابع مشابه
Low-complexity Big Video Data Recording Algorithms for Urban Surveillance Systems
Big Video data analytics and processing are becoming increasingly important research areas because of infinite generation of massive video data volumes all over the world. In this paper, by utilizing Bayesianbased importance analysis, we propose a set of novel, simple but effective video recording methodologies and intelligent algorithms to solve the so-called big video data volume problem in u...
متن کاملAdaptive Caching Algorithms for Big Data Systems
Today’s Big Data platforms have enabled the democratization of data by allowing data sharing among various data processing frameworks and applications that run in the same platform. This data and resource sharing, combined with the fact that most applications tend to access a hot set of the data has led to the development of external, in-memory, distributed caching frameworks. In this paper, we...
متن کاملFusion of Face Recognition Algorithms for Video-based Surveillance Systems
It is widely acknowledged that face recognition could play an important role in advanced video-based surveillance systems, mainly because it is non-intrusive and does not require people cooperation. Unfortunately, face recognition algorithms showed to suffer a lot from the high variability of environmental conditions (e.g., variations of lighting, face pose and scale). This currently limits the...
متن کاملData Compression Systems for Home-Use Digital Video Recording
Newly developed communication-and information networks offer a large number of services which make use of image data, leading to an increasing demand for image storage systems. This paper focuses on a new emerging technology, namely image data compression techniques for digital recording. image coding for storage equipment covers a large variety of systems because the applications differ consid...
متن کاملShingled Magnetic Recording for Big Data Applications
Acknowledgements: We would like to thank Seagate for funding this project through the Data Storage Systems Center at CMU. We also thank the members and companies of the PDL Consortium (including Abstract Modern Hard Disk Drives (HDDs) are fast approaching the superparamagnetic limit forcing the storage industry to look for innovative ways to transition from traditional magnetic recording to Hea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Data Mining & Knowledge Management Process
سال: 2016
ISSN: 2231-007X,2230-9608
DOI: 10.5121/ijdkp.2016.6601