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Hironori Hidaka

dblp:247/5996 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 67% Computational photography and imaging · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
3d reconstruction
0.412019
Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion · ICCV 2019
Geometric modeling and processing › 3d reconstruction
structure from motion
0.412019
Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion · ICCV 2019

Methods — techniques the papers use, named apart from their topics

structured light · 0.4spectral reflectance estimation · 0.4multispectral imaging · 0.4
YearPublicationVenuePosition
2019 Pro-Cam SSfM: Projector-Camera System for Structure and Spectral Reflectance From Motion
abstract
In this paper, we propose a novel projector-camera system for practical and low-cost acquisition of a dense object 3D model with the spectral reflectance property. In our system, we use a standard RGB camera and leverage an off-the-shelf projector as active illumination for both the 3D reconstruction and the spectral reflectance estimation. We first reconstruct the 3D points while estimating the poses of the camera and the projector, which are alternately moved around the object, by combining multi-view structured light and structure-from-motion (SfM) techniques. We then exploit the projector for multispectral imaging and estimate the spectral reflectance of each 3D point based on a novel spectral reflectance estimation model considering the geometric relationship between the reconstructed 3D points and the estimated projector positions. Experimental results on several real objects demonstrate that our system can precisely acquire a dense 3D model with the full spectral reflectance property using off-the-shelf devices.
Yusuke Monno, Hironori Hidaka, Masatoshi Okutomi
ICCV3