Exploring local regularities for 3D object recognition

Tian, Huaiwen and Qin, Sheng-feng (2016) Exploring local regularities for 3D object recognition. Chinese Journal of Mechanical Engineering, 29 (6). pp. 1104-1113. ISSN 1000-9345

Full text not available from this repository. (Request a copy)
Official URL: http://dx.doi.org/10.3901/CJME.2016.0721.085

Abstract

In order to find better simplicity measurements for 3D object recognition, a new set of local regularities is developed and tested in a stepwise 3D reconstruction method, including localized minimizing standard deviation of angles(L-MSDA), localized minimizing standard deviation of segment magnitudes(L-MSDSM), localized minimum standard deviation of areas of child faces (L-MSDAF), localized minimum sum of segment magnitudes of common edges (L-MSSM), and localized minimum sum of areas of child face (L-MSAF). Based on their effectiveness measurements in terms of form and size distortions, it is found that when two local regularities: L-MSDA and L-MSDSM are combined together, they can produce better performance. In addition, the best weightings for them to work together are identified as 10% for L-MSDSM and 90% for L-MSDA. The test results show that the combined usage of L-MSDA and L-MSDSM with identified weightings has a potential to be applied in other optimization based 3D recognition methods to improve their efficacy and robustness.

Item Type: Article
Uncontrolled Keywords: stepwise 3D reconstruction, localized regularities, 3D object recognition, polyhedral objects, line drawing
Subjects: W200 Design studies
Department: Faculties > Arts, Design and Social Sciences > Design
Depositing User: Ay Okpokam
Date Deposited: 07 Dec 2016 10:32
Last Modified: 24 Oct 2017 08:18
URI: http://nrl.northumbria.ac.uk/id/eprint/28826

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence