Deep Learning for Object Detection and Segmentation in Videos: Toward an Integration With Domain Knowledge

Athina Ilioudi*, Azita Dabiri, Ben J. Wolf, Bart De Schutter

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

13 Downloads (Pure)

Abstract

Deep learning has enabled the rapid expansion of computer vision tasks from image frames to video segments. This paper focuses on the review of the latest research in the field of computer vision tasks in general and on object localization and identification of their associated pixels in video frames in particular. After performing a systematic analysis of the existing methods, the challenges related to computer vision tasks are presented. In order to address the existing challenges, a hybrid framework is proposed, where deep learning methods are coupled with domain knowledge. An additional feature of this survey is that a review of the currently existing approaches integrating domain knowledge with deep learning techniques is presented. Finally, some conclusions on the implementation of hybrid architectures to perform computer vision tasks are discussed.
Original languageEnglish
Pages (from-to)34562-34576
JournalIEEE Access
Volume10
DOIs
Publication statusPublished - 2022

Keywords

  • Computer vision
  • object detection
  • deep learning
  • theory-guided data science

Fingerprint

Dive into the research topics of 'Deep Learning for Object Detection and Segmentation in Videos: Toward an Integration With Domain Knowledge'. Together they form a unique fingerprint.

Cite this