eprintid: 1529303
rev_number: 20
eprint_status: archive
userid: 608
dir: disk0/01/52/93/03
datestamp: 2016-11-23 15:59:37
lastmod: 2021-09-20 22:16:31
status_changed: 2016-11-23 15:59:37
type: article
metadata_visibility: show
creators_name: Wong, Y-S
creators_name: Chu, H-K
creators_name: Mitra, NJ
title: SmartAnnotator An Interactive Tool for Annotating Indoor RGBD Images
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Science & Technology, Technology, Computer Science, Software Engineering, Computer Science
note: This is the peer reviewed version of the following article: Wong, Y-S; Chu, H-K; Mitra, NJ; (2015) SmartAnnotator An Interactive Tool for Annotating Indoor RGBD Images. Computer Graphics Forum, 34 (2) pp. 447-457, which has been published in final form at: http://dx.doi.org/10.1111/cgf.12574. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving (http://olabout.wiley.com/WileyCDA/Section/id-828039.html#terms).
abstract: RGBD images with high quality annotations, both in the form of geometric (i.e., segmentation) and structural (i.e., how do the segments mutually relate in 3D) information, provide valuable priors for a diverse range of applications in scene understanding and image manipulation. While it is now simple to acquire RGBD images, annotating them, automatically or manually, remains challenging. We present SmartAnnotator, an interactive system to facilitate annotating raw RGBD images. The system performs the tedious tasks of grouping pixels, creating potential abstracted cuboids, inferring object interactions in 3D, and generates an ordered list of hypotheses. The user simply has to flip through the suggestions for segment labels, finalize a selection, and the system updates the remaining hypotheses. As annotations are finalized, the process becomes simpler with fewer ambiguities to resolve. Moreover, as more scenes are annotated, the system makes better suggestions based on the structural and geometric priors learned from previous annotation sessions. We test the system on a large number of indoor scenes across different users and experimental settings, validate the results on existing benchmark datasets, and report significant improvements over low-level annotation alternatives. (Code and benchmark datasets are publicly available on the project page.)
date: 2015-05
date_type: published
publisher: WILEY-BLACKWELL
official_url: http://dx.doi.org/10.1111/cgf.12574
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
article_type_text: Article
verified: verified_manual
elements_id: 939822
doi: 10.1111/cgf.12574
lyricists_name: Mitra, Niloy
lyricists_id: NMITR19
actors_name: Mitra, Niloy
actors_name: Allington-Smith, Dominic
actors_id: NMITR19
actors_id: DAALL44
actors_role: owner
actors_role: impersonator
full_text_status: public
publication: Computer Graphics Forum
volume: 34
number: 2
pagerange: 447-457
pages: 11
event_location: Zurich, SWITZERLAND
issn: 0167-7055
citation:        Wong, Y-S;    Chu, H-K;    Mitra, NJ;      (2015)    SmartAnnotator An Interactive Tool for Annotating Indoor RGBD Images.                   Computer Graphics Forum , 34  (2)   pp. 447-457.    10.1111/cgf.12574 <https://doi.org/10.1111/cgf.12574>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1529303/1/Mitra_1403.5718v1.pdf