TY  - CONF
N2  - In this paper, we propose possibility for reconstruction of surface of an underwater object or 3D scene reconstruction of an underwater environment using an economical RGB-D sensor such as Microsoft Kinect. Reconstructing the 3D surface of an underwater object is a challenging task due to degraded quality of underwater images. There are various reasons of quality degradation of underwater images i.e., non-uniform illumination of light on the surface of objects, scattering and absorption effects. Particles and impurities present in underwater produces Gaussian noise on the captured underwater optical images which degrades the quality of images. However, using depth sensors, as a cost effective alternative, we aim to show that underwater 3D scene reconstruction is possible with sight tradeoffs on accuracy but major cost saving. The acquired depth data is proposed to be processed by applying real-time mesh generating techniques from the acquired point cloud. The experimental result aims to show that the proposed method reconstructs 3D surface of underwater objects accurately using captured underwater depth images. © 2016 IEEE.
ID  - scholars8955
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011982881&doi=10.1109%2fICIAS.2016.7824132&partnerID=40&md5=5de1eb740ae93e1e4acefa1b99d233bb
KW  - Cost effectiveness; Costs; Gaussian noise (electronic); Geometrical optics; Image processing; Three dimensional computer graphics
KW  -  3D scene reconstruction; Microsoft kinect; Non-uniform illumination; Quality degradation; Scattering and absorption; Scene reconstruction; Underwater environments; Underwater objects
KW  -  Surface reconstruction
PB  - Institute of Electrical and Electronics Engineers Inc.
A1  - Anwer, A.
A1  - Ali, S.S.A.
A1  - Meriaudeau, F.
SN  - 9781509008452
AV  - none
N1  - cited By 7; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970
TI  - Underwater online 3D mapping and scene reconstruction using low cost kinect RGB-D sensor
Y1  - 2017///
ER  -