Tracking features in image sequences with Kalman filtering, global optimization, mahalanobis distance and a management model

• Type: Article in International Scientific Journal
• Date: 2009

Authors

Raquel R. Pinho (Author) FEUP; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES

Vol. 46 No. 1

Pages: 51-75

ISSN: 1526-1492

Publisher: Tech Science Press

Indexing

ISI Web of Knowledge - 14 Citations

ISI Web of Science

Scopus - 20 Citations

Scientific classification

FOS: Engineering and technology > Other engineering and technologies

CORDIS: Technological sciences > Technology > Computer technology > Image processing

Other information

Authenticus ID: P-003-JDG

Abstract (EN): This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features’ movement in every image frame. So as to integrate the measurements obtained from each image into the Kalman filter, a data optimization process has been adopted to achieve the best global correspondence set. The proposed criterion minimizes the cost of global matching, which is based on the Mahalanobis distance. A management model is employed to manage the features being tracked. This model adequately deals with problems related to the occlusion of the tracked features, the appearance of new features, as well as optimizing the computational resources used. Experimental results obtained through the use of the proposed tracking framework are presented.

Language: English

Type (Professor's evaluation): Scientific