Measuring the effects of temporal coherence in depth estimation for dynamic scenes

Iraklis Tsekourakis, Philippos Mordohai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper presents a new algorithm for enforcing temporal coherence on depth estimation from multi-view videos of dynamic scenes as well as the first substantial quantitative evaluation of the improvement in depth estimation accuracy due to temporal coherence. The proposed algorithm is generally applicable and practical since it bypasses explicit scene flow estimation, which has a very large state space, and relies only on optical flow which is used to impose soft constraints on depth estimation for the next frame. As a result, our algorithm is applicable to scenes with large depth and motion ranges. The output is a sequence of depth maps that can be used for novel view synthesis among other applications. While it is intuitive that enforcing temporal coherence should improve the accuracy of depth estimation, this improvement has never been assessed quantitatively due to the lack of data with ground truth. To overcome this limitation we use the image prediction error as the criterion and show that the benefits of temporal coherence are significant on a diverse set of multi-view video sequences.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Pages2867-2875
Number of pages9
ISBN (Electronic)9781728125060
DOIs
StatePublished - Jun 2019
Event32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 - Long Beach, United States
Duration: 16 Jun 201920 Jun 2019

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2019-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Country/TerritoryUnited States
CityLong Beach
Period16/06/1920/06/19

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