Video Object Detection Method Using Single-Frame Detection and Motion Vector Tracking

Masato Nohara, Hiroaki Nishi

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

Abstract

Video traffic on the Internet has been increasing rapidly and accounts for a large percentage of the total traffic. To process the increasing number of videos, edge computing is preferable for load balancing and bandwidth reduction. However, edge areas have less computational resources than cloud areas, and high-performance GPUs for processing videos at high speed are not always present. Therefore, a memory-saving and high-Throughput video analysis method is necessary for analyzing videos in edge areas. In this paper, a video object detection method using single-frame detection and motion vector tracking is proposed. This method is classified as a pixel and compressed domain analysis method and is realized by compensating motion using the motion vectors that already exist in the compressed domain. This method is divided into two processes: CNN-based object detection and motion vector-based object detection. In addition, a network-Transparent platform for video reconstruction in edge areas is constructed. The network-Transparent service can be installed without modifying the existing end-device network settings, network configuration, and routing. The platform enables video object detection services to be added on without modification of these settings.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 18th International Conference on Industrial Informatics, INDIN 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-125
Number of pages7
ISBN (Electronic)9781728149646
DOIs
Publication statusPublished - 2020 Jul 20
Event18th IEEE International Conference on Industrial Informatics, INDIN 2020 - Virtual, Warwick, United Kingdom
Duration: 2020 Jul 212020 Jul 23

Publication series

NameIEEE International Conference on Industrial Informatics (INDIN)
Volume2020-July
ISSN (Print)1935-4576

Conference

Conference18th IEEE International Conference on Industrial Informatics, INDIN 2020
Country/TerritoryUnited Kingdom
CityVirtual, Warwick
Period20/7/2120/7/23

Keywords

  • compressed domain analysis
  • edge computing
  • motion vector
  • moving detection
  • network transparency
  • video object detection

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

Fingerprint

Dive into the research topics of 'Video Object Detection Method Using Single-Frame Detection and Motion Vector Tracking'. Together they form a unique fingerprint.

Cite this