Title :
Extracting good features for motion estimation
Author :
Tan, Yap-Peng ; Kulkarni, Sanjeev R. ; Ramadge, Peter J.
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
Abstract :
Selecting image features whose correspondences can be accurately established between images is a key step in many image processing problems, such as camera and object motion estimation, 3D structure reconstruction, and image registration. In this paper, we present a new method of selecting good features for estimating motion from images. Our approach is different from other existing approaches in that we formulate feature tracking as a signal parameter estimation problem, give a quantitative measure of feature quality in terms of how accurately the feature can be tracked, and can adaptively select features with different shapes and sizes which depend on the local variations of the images. Through the analysis of this feature quality measure, we can characterize the basic properties that allow a feature to be well tracked. Some experimental results are shown to demonstrate the advantages and robustness of the proposed method
Keywords :
feature extraction; motion estimation; parameter estimation; tracking; 3D structure reconstruction; camera motion estimation; feature quality; feature quality measure; feature tracking; good features extraction; image features; image registration; local variation; motion estimation; object motion estimation; shapes; signal parameter estimation problem; size; Cameras; Feature extraction; Image processing; Image reconstruction; Image registration; Motion estimation; Parameter estimation; Robustness; Shape measurement; Size measurement;
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
DOI :
10.1109/ICIP.1996.559446