Paper Info
Title
Real-Time Logo Recognition From Live Video Streams Using An Elastic Cloud Platform
Abstract
Real-time logo recognition from a live video stream has promising commercial applications. For example, a sports video website broadcasting a live soccer match could show advertisements of brands when their logos appear in the video. Although logo recognition is a well-studied problem, the vast majority of previous work focuses on recognition accuracy, rather than system efficiency. Consequently, existing methods cannot recognize logos in real-time, especially when a large number of logos appear in the video. Motivated by this, we propose a general framework that converts an offline logo detection method to a real-time one, by utilizing the massive parallel processing capabilities of an elastic cloud platform. The main challenge is to obtain high scalability, meaning that logo recognition efficiency keeps improving as we add more computing resources, as well as elasticity, meaning that the resource allocation is guided by the current workload rather than the peak load. The proposed framework achieves these by balancing workload, elastically provisioning resources, minimizing communication overhead, and eliminating performance bottlenecks in the system. Experiments using real data demonstrate the high efficiency, scalability and elasticity of the proposed solution.
Year
DOI
Venue
2016
10.1007/978-3-319-39958-4_37
Web-Age Information Management, Pt II
Keywords
Field
DocType
Real-time streams, Logo detection, Elastic cloud platform
Data mining,Broadcasting,Computer science,Workload,Massively parallel,Logo,Provisioning,Real-time computing,Resource allocation,Logo recognition,Multimedia,Scalability
Conference
Volume
ISSN
Citations 
9659
0302-9743
0
PageRank 
References 
Authors
0.34
15
3
Name
Order
Citations
PageRank
Jianbing Ding1684.72
Hongyang Chao249536.96
Mansheng Yang390.81