Semantic Segmentation of UAV Videos based on Temporal Smoothness in Conditional Random Fields

S. Girisha, M. M. Manohara Pai, Ujjwal Verma, Radhika M. Pai

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

Abstract

Video semantic segmentation is increasingly becoming a vital factor in many Unmanned Aerial Vehicle (UAV) drone-based applications such as surveillance, scene understanding etc. However, the accuracy of video semantic segmentation systems are greatly dependent on temporal consistent labelling. In this regard, a new approach for semantic segmentation of UAV videos is proposed by utilizing U-Net and Conditional Random Field. This algorithm incorporates temporal information to ensure temporal consistency in labelling. This work shows that Conditional Random Field algorithm along with temporal cues reduces the false positives and increases the accuracy of semantic segmentation. Moreover, the proposed method is quantitatively evaluated on ManipalUAVid dataset and achieved a mIoU of 0.88 which is significantly greater than traditional image based segmentation method such as U-Net.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages241-245
Number of pages5
ISBN (Electronic)9781728198859
DOIs
Publication statusPublished - 30-10-2020
Event2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Udupi, India
Duration: 30-10-202031-10-2020

Publication series

Name2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings

Conference

Conference2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020
CountryIndia
CityUdupi
Period30-10-2031-10-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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