Eigenvalue based corner detection is known to be effective in detecting corners of objects in noise. In this paper, a corner detection technique based on including the orientation and the angle of the corner in addition to its eigenvalue is introduced. It is shown that both orientation and corner information improve the detectability of corners. Moreover, corners that have been selected via the new technique are more likely to be detected in subsequent frames and therefore improve the performance of an object tracker. This modification only adds a minor computational load to our tracking schemé. Real and synthetic images are used to evaluate the detection performance as well as their effect on tracking.

Date Published: 9 August 2004
PDF: 12 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.541476

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)