Protuberance of depth: Detecting interest points from a depth image

Yuseok Ban, Sangyoun Lee

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Detecting distinctive interest points in a scene or an object allows estimating which details a human finds interesting in advance to understand the scene or the object. This also forms the important basis of a variety of latter tasks related to visual detection and tracking. In this paper, we propose a simple but effective approach to extract the feature from a depth image, namely Protuberance of Depth (PoD). The proposed approach semantically explores the inherent feature representing three-dimensional protuberance by using depth which only contains two-dimensional distance information. Our approach directly allows detecting consistent interest points in a depth image. The experimental results show that our method is effective against the isometric deformation and rotation of a depth region and is applicable for real-time applications.

Original languageEnglish
Article number102927
JournalComputer Vision and Image Understanding
Publication statusPublished - 2020 May

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Inc.

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition


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