Title :
An Adaptive Solution for Large-Scale, Cross-Video and Real-Time Visual Analytics
Author :
Xiao Hu ; Zhihong Yu ; Huan Zhou ; Hongbo Lv ; Zhipeng Jiang ; Xiang Zhou
Author_Institution :
Intel Asia-Pacific Res. & Dev., Ltd., Shanghai, China
Abstract :
This paper aims at a new challenge caused by a specific type of real-life problems that require to not only process tremendous videos, dig out cross-video information, but also guarantee a real-time responsiveness to the user. Moreover, users want to adapt the resources to the actual amount of visual objects, rather than to the number of videos, in order to better match resource consumption to the true business needs. All the state-of-the-art solutions cannot meet these requirements altogether, while this paper developed a series of techniques to address each specific problem, and then proposed a new adaptive solution for large-scale, cross-video, and real-time visual analytics.
Keywords :
image matching; video signal processing; adaptive framework; cross-video information; large-scale cross-video analytics; real-time user responsiveness; real-time visual analytics; resource consumption matching; video processing; visual objects; Decoding; Licenses; Real-time systems; Streaming media; Vehicles; Visual analytics; adaptability; cross-video; real-time; visual analytics;
Conference_Titel :
Multimedia Big Data (BigMM), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-8687-3
DOI :
10.1109/BigMM.2015.57