• DocumentCode
    1710214
  • Title

    HVPI: Extending Hadoop to Support Video Analytic Applications

  • Author

    Xiaomeng Zhao ; Huadong Ma ; Haitao Zhang ; Yi Tang ; Yue Kou

  • Author_Institution
    Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2015
  • Firstpage
    789
  • Lastpage
    796
  • Abstract
    Hadoop is widely deployed distributed computing framework and makes creating distributed applications much easier. However, unlike text data, there is no existing video r/w interface for Hadoop, and many existing video analytic applications implemented in C/C++ are not compatible with Hadoop framework. In this paper, we propose an open source Hadoop video processing interface HVPI to extend Hadoop to support video analytic applications. It provides easy-to-use video r/w interface for developers to quickly build large-scale video analytic applications based on Hadoop, and native processing interface to help users easily port existing video analytic applications written in C/C++ into Hadoop platform. We also present two typical use cases of HVPI and do experiments based on them. Experimental results demonstrate that the applications built based on HVPI are both scalable and efficient.
  • Keywords
    parallel processing; video signal processing; C/C++ language; HVPI; Hadoop framework; distributed computing framework; open source Hadoop video processing interface; video analytic applications; video read-write interface; Cameras; Java; Libraries; Ports (Computers); Streaming media; Surveillance; Writing; JNI; distributed video processing; hadoop; hadoop pipes; hadoop steaming; video analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
  • Conference_Location
    New York City, NY
  • Print_ISBN
    978-1-4673-7286-2
  • Type

    conf

  • DOI
    10.1109/CLOUD.2015.109
  • Filename
    7214119