A study on the effects of RGB-D database scale and quality on depth analogy performance

Sunok Kim, Youngjung Kim, Kwanghoon Sohn

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

2 Citations (Scopus)


In the past few years, depth estimation from a single image has received increased attentions due to its wide applicability in image and video understanding. For realizing these tasks, many approaches have been developed for estimating depth from a single image based on various depth cues such as shading, motion, etc. However, they failed to estimate plausible depth map when input color image is derived from different category in training images. To alleviate these problems, data-driven approaches have been popularly developed by leveraging the discriminative power of a large scale RGB-D database. These approaches assume that there exists appearance- depth correlation in natural scenes. However, this assumption is likely to be ambiguous when local image regions have similar appearance but different geometric placement within the scene. Recently, a depth analogy (DA) has been developed by using the correlation between color image and depth gradient. DA addresses depth ambiguity problem effectively and shows reliable performance. However, no experiments are conducted to investigate the relationship between database scale and the quality of the estimated depth map. In this paper, we extensively examine the effects of database scale and quality on the performance of DA method. In order to compare the quality of DA, we collect a large scale RGB-D database using Microsoft Kinect v1 and Kinect v2 on indoor and ZED stereo camera on outdoor environments. Since the depth map obtained by Kinect v2 has high quality compared to that of Kinect v1, the depth maps from the database from Kinect v2 are more reliable. It represents that the high quality and large scale RGB-D database guarantees the high quality of the depth estimation. The experimental results show that the high quality and large scale training database leads high quality estimated depth map in both indoor and outdoor scenes.

Original languageEnglish
Title of host publicationThree-Dimensional Imaging, Visualization, and Display 2016
EditorsBahram Javidi, Jung-Young Son
ISBN (Electronic)9781510601086
Publication statusPublished - 2016
EventThree-Dimensional Imaging, Visualization, and Display 2016 Conference - Baltimore, United States
Duration: 2016 Apr 182016 Apr 20

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherThree-Dimensional Imaging, Visualization, and Display 2016 Conference
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2016 SPIE.

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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