SciELO - Scientific Electronic Library Online

 
vol.24 issue2RuDES: a Semantic Method for Rules Dependency ExtractionA Novel Methodology to Study Synchrony, Causality and Delay in EEG Data author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

DIAZ, Andrés; PAZ, Lina; PINIES, Pedro  and  CAICEDO, Eduardo. Depth Map Building and Enhancement using a Monocular Camera, Shape Priors and Variational Methods. Comp. y Sist. [online]. 2020, vol.24, n.2, pp.781-796.  Epub Oct 04, 2021. ISSN 2007-9737.  https://doi.org/10.13053/cys-24-2-3021.

We present a monocular system that uses shape priors for improving the quality of estimated depth maps, specially in the region of an object of interest, when the environment presents complex conditions like changes in light, with low-textured, very reflective and translucent objects. A depth map is built by solving a non-convex optimization problem using the primal-dual algorithm and a coupling term. The energy functional consists of a photometric term for a set of images with common elements in the scene and a regularization term that allows smooth solutions. The camera is moved by hand and tracked using ORB-SLAM2. The resulting depth map is enhanced by integrating, with a novel variational formulation, depth data coming from the 3D model that best fits to observed data, optimized w.r.t. shape, pose and scale (shape prior). We also present an alternative algorithm that simultaneously builds a depth map and integrates a previously estimated shape prior. We quantify the improvements in accuracy and in noise reduction of the final depth map.

Keywords : Dense mapping; shape priors; variational methods; primal-dual algorithm; depth integration; depth denoising.

        · text in English