Object proposal via depth connectivity constrained grouping

Yuantian Wang, Lei Huang, Tongwei Ren, Sheng Hua Zhong, Yan Liu, Gangshan Wu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Object proposal aims to detect category-independent object candidates with a limited number of bounding boxes. In this paper, we propose a novel object proposal method on RGB-D images with the constraint of depth connectivity, which can improve the key techniques in grouping based object proposal effectively, including segment generation, hypothesis expansion and candidate ranking. Given an RGB-D image, we first generate segments using depth aware hierarchical segmentation. Next, we combine the segments into hypotheses hierarchically on each level, and further expand these hypotheses to object candidates using depth connectivity constrained region growing. Finally, we score the object candidates based on their color and depth features, and select the ones with the highest scores as the object proposal result. We validated the proposed method on the largest RGB-D image data set for object proposal, and our method is superior to the state-of-the-art methods.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
EditorsBing Zeng, Hongliang Li, Qingming Huang, Abdulmotaleb El Saddik, Shuqiang Jiang, Xiaopeng Fan
Number of pages11
ISBN (Print)9783319773827
Publication statusPublished - 1 Jan 2018
Event18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, China
Duration: 28 Sept 201729 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10736 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th Pacific-Rim Conference on Multimedia, PCM 2017


  • Constrained grouping
  • Depth connectivity
  • Object proposal
  • RGB-D image

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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