caa a22 4500 60544658X CHVBK 20210128100127.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11042-014-2185-x doi (NATIONALLICENCE)springer-10.1007/s11042-014-2185-x GPU-based MapReduce for large-scale near-duplicate video retrieval [Elektronische Daten] [Hanli Wang, Fengkuangtian Zhu, Bo Xiao, Lei Wang, Yu-Gang Jiang] With the exponential growth of multimedia data, people are overwhelmed with massive amount of online videos, of which Near-Duplicate Videos (NDVs) occupy a large portion. In this paper, we present a novel framework for NDV retrieval, which explores the parallel power of two promising techniques: Graphics Processing Unit (GPU) and MapReduce. With the power of the proposed framework, various key algorithms in the field of computer vision, such as K-Means clustering, bag of features, inverted file index with hamming embedding and weak geometric consistency, are applied to NDV retrieval. Experimental results on the benchmark CC_WEB_VIDEO NDV dataset demonstrate that the proposed framework can significantly speed up processing huge amounts of video repositories. Springer Science+Business Media New York, 2014 Near-duplicate video retrieval nationallicence Mapreduce nationallicence GPU nationallicence Hadoop nationallicence Wang Hanli Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut Zhu Fengkuangtian Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut Xiao Bo Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut Wang Lei Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut Jiang Yu-Gang School of Computer Science, Fudan University, 201203, Shanghai, People's Republic of China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/23(2015-12-01), 10515-10534 1380-7501 74:23<10515 2015 74 11042 https://doi.org/10.1007/s11042-014-2185-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-2185-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Hanli Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Zhu Fengkuangtian Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Xiao Bo Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Wang Lei Department of Computer Science & Technology and Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, 200092, Shanghai, People's Republic of China aut NATIONALLICENCE 700 1- Jiang Yu-Gang School of Computer Science, Fudan University, 201203, Shanghai, People's Republic of China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/23(2015-12-01), 10515-10534 1380-7501 74:23<10515 2015 74 11042