Distributed Feature Extraction on Apache Spark for Human Action Recognition

Nguyen Anh Tu, Thien Huynh-The, Kok Seng Wong, Dinh Mao Bui, Young Koo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Local feature extraction is one of the most important tasks to build robust video representation in human action recognition. Recent advances in computing visual features, especially deep-learned features, have achieved excellent performance on a variety of action datasets. However, the extraction process is computing-intensive and extremely time-consuming when conducting it on large-scale video data. Consequently, to extract video features over big data, most of the existing methods that run on single machine become inefficient due to the limit of computation power and memory capacity. In this paper, we propose the elastic solutions for feature extraction based on the Spark framework. Particularly, exploiting the in-memory computing capability of Spark, the process of computing features are parallelized by partitioning video data into videos or frames and place them into resilient distributed datasets (RDDs) for the subsequent processing. Then, we present the parallel algorithms to extract the state-of-the-art deep-learned features on the Spark cluster. Subsequently, using the distributed encoding, the extracted features are aggregated into the global representation which is fed into the learned classifier to recognize actions in videos. Experimental results on a benchmark dataset demonstrate that our proposed methods can significantly speed up the extraction process and achieve the promising scalability performance.

Original languageEnglish
Title of host publicationProceedings of the 2020 14th International Conference on Ubiquitous Information Management and Communication, IMCOM 2020
EditorsSukhan Lee, Hyunseung Choo, Roslan Ismail
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728154534
DOIs
Publication statusPublished - Jan 2020
Event14th International Conference on Ubiquitous Information Management and Communication, IMCOM 2020 - Taichung, Taiwan
Duration: Jan 3 2020Jan 5 2020

Publication series

NameProceedings of the 2020 14th International Conference on Ubiquitous Information Management and Communication, IMCOM 2020

Conference

Conference14th International Conference on Ubiquitous Information Management and Communication, IMCOM 2020
CountryTaiwan
CityTaichung
Period1/3/201/5/20

Keywords

  • deep learning
  • Human action recognition
  • local feature
  • MapReduce
  • Spark

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Communication

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