Robust matching in real-time 3D model-based tracking

Author

Li, Zheng ; Wang, Han

Author_Institution

Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore

Volume

1

fYear

1997

fDate

27-23 May 1997

Firstpage

137

Abstract

In this paper, a new model-based tracking algorithm is proposed for real time performance. The matching process includes two aspects of: feature extraction using local minimum energy; and global matching of a known 3D model against the projected features. The algorithm is robust to change in lighting and backgrounds. The small motion hypothesis is used for fitting of feature energy which is defined as the negative absolute value of the edge strength. An autoregressive AR(1) model is employed for detecting incorrect matches in terms of the feature energy

Keywords

edge detection; feature extraction; image matching; lighting; motion estimation; performance evaluation; real-time systems; statistical analysis; tracking; autoregressive model; backgrounds; edge detection; edge strength; feature energy; feature extraction; global matching; lighting; local minimum energy; motion estimation; projected features; real time performance; real-time 3D model-based tracking; robust matching; small motion hypothesis; Bandwidth; Cameras; Change detection algorithms; Computer vision; Hardware; Image edge detection; Image processing; Power engineering and energy; Robustness; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3755-7

Type

conf

DOI

10.1109/KES.1997.616874

Filename

616874