18 August 2011 Fusing edges and feature points for robust target tracking
Author Affiliations +
Feature points and object edges are two kinds of primitives which are frequently used in target tracking algorithms. Feature points can be easily localized in an image. Their correspondences between images can be detected accurately. They can adapt to wide baseline transformations. However, feature points are not so stable that they are fragile to changes in illumination and viewpoint. On the contrary, object edges are stable under a very wide range of illumination and viewpoint changes. Unfortunately, edge-based algorithms often fail in the presence of highly textured targets and clutter which produce too many irrelevant edges. We found that both edge-based and point-based tracking have failure modes which are complementary. Based on this analysis, we propose a novel tracking algorithm which fuses point and edge features. Our tracking algorithm uses feature points matching to track object first, and then uses the transformation parameters archived in the first step to initialize the edge tracking. By this means, our algorithm alleviates the disturbance of irrelevant edges. Then, we use the texture boundary detection algorithm to find the precise object boundary. Texture boundary detection is different from the conventional gradient-based edge detection which can directly compute the most probable location of a texture boundary on the search line. Therefore, it is very fast and can be incorporated into a real-time tracking algorithm. Experimental results show that our tracking algorithm has outstanding tracking accuracy and robustness.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Li, Wei Li, Ze-lin Shi, Ze-lin Shi, Jian Yin, Jian Yin, Qing-hai Ding, Qing-hai Ding, } "Fusing edges and feature points for robust target tracking", Proc. SPIE 8194, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, 81942K (18 August 2011); doi: 10.1117/12.900721; https://doi.org/10.1117/12.900721


Image Edge Tracking via Ant Colony Optimization
Proceedings of SPIE (April 09 2018)
An improved matching method base on SURF
Proceedings of SPIE (August 08 2018)
ATR Evaluation: Cautionary Comments
Proceedings of SPIE (May 02 1988)
Using physical color models in 3-D machine vision
Proceedings of SPIE (July 31 1990)
Using color to segment images of 3-D scenes
Proceedings of SPIE (February 28 1991)

Back to Top