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A fuzzy-based approach for approximating depth information in RGB-D images

Nguyen, M.U. and Dao, T.T. and Ngo, L.T. (2015) A fuzzy-based approach for approximating depth information in RGB-D images. In: 7th IEEE Symposium on Computational Intelligence for Security and Defense Applications, CISDA 2014, 14 December 2014 through 17 December 2014.

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Abstract

Robot navigation has several security and defence applications. The major technical challenges include measuring the distance between a robot and its surrounding obstacles and modelling the sensing environment. Existing methods using stereo cameras, laser sensors, and low-cost MS Kinect cameras have been suggested for the problems. In this paper, we propose a fuzzy-based approach for approximating the missing depth values in RGB-D images collected from a MS Kinect camera. By investigating different noise models, the missing information, and the relations between the depth and colour images, the proposed approach produces an accurate approximation for missing depth values, which enhances results of subsequent steps in RGB-D image processing. © 2014 IEEE.

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculties > Faculty of Information Technology
Identification Number: 10.1109/CISDA.2014.7035636
Uncontrolled Keywords: Cameras; Image enhancement; Robots; Defence applications; Depth information; Missing information; Noise models; Robot navigation; Stereo cameras; Surrounding obstacles; Technical challenges; Stereo image processing
Additional Information: Conference code: 110865. Language of original document: English.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9935

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