SIFT Features Tracking for Video Stabilization

Authors:
Sebastiano Battiato;Giovanni Gallo;Giovanni Puglisi;Salvatore Scellato
Affiliations:
University of Catania, Italy;University of Catania, Italy;University of Catania, Italy;Scuola Superiore di Catania, Italy
Venue:
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Year:
2007

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Abstract

This paper presents a video stabilization algorithm based on the extraction and tracking of Scale Invariant Feature Transform features through video frames. Implementation of SIFT operator is analyzed and adapted to be used in a feature-based motion estimation algorithm. SIFT features are extracted from video frames and then their trajectory is evaluated to estimate interframe motion. A modified version of Iterative Least Squares method is adopted to avoid estimation errors and features are tracked as they appear in nearby frames to improve video stability. Intentional camera motion is eventually filtered with Adaptive Motion Vector Integration. Results confirm the effectiveness of the method.