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Depth from Defocus via Active Quasi-random Point Projections

Authors :
Francis Li
Avery Ma
Alexander Wong
Source :
Journal of Computational Vision and Imaging Systems. 2
Publication Year :
2016
Publisher :
University of Waterloo, 2016.

Abstract

Depth sensing has many practical applications in vision-relatedtasks. While many different depth measurement techniques existand depth camera technologies are constantly being advanced, activedepth sensing still rely on specialized hardware that are highlycomplex and costly. Motivated by this, we present a novel techniquefor inferring depth measurements via depth from defocus usingactive quasi-random point projection patterns. A quasi-randompoint projection pattern is projected onto the scene of interest, andeach projection point in the image captured by a camera is analysedusing a calibration model to estimate the depth at that point.The proposed method has a relatively simple setup, consisting of acamera and a projector, and enables depth inference from a singlecapture. Furthermore, the use of a quasi-random projection patterncan allow us to leverage compressive sensing theory to producefull depth maps in future applications. Experimental resultsshow the proposed system has strong potential for enabling activedepth sensing in a simple, efficient manner.

Details

ISSN :
25620444
Volume :
2
Database :
OpenAIRE
Journal :
Journal of Computational Vision and Imaging Systems
Accession number :
edsair.doi...........05e1f5b4fee2957fb18d42207ff92eed
Full Text :
https://doi.org/10.15353/vsnl.v2i1.96