Paper
7 May 2003 Probabilistic video stabilization using Kalman filtering and mosaicing
Author Affiliations +
Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476436
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
The removal of unwanted, parasitic vibrations in a video sequence induced by camera motion is an essential part of video acquisition in industrial, military and consumer applications. In this paper, we present a new image processing method to remove such vibrations and reconstruct a video sequence void of sudden camera movements. Our approach to separating unwanted vibrations from intentional camera motion is based on a probabilistic estimation framework. We treat estimated parameters of interframe camera motion as noisy observations of the intentional camera motion parameters. We construct a physics-based state-space model of these interframe motion parameters and use recursive Kalman filtering to perform stabilized camera position estimation. A six-parameter affine model is used to describe the interframe transformation, allowing quite accurate description of typical scene changes due to camera motion. The model parameters are estimated using a p-norm-based multi-resolution approach. This approach is robust to model mismatch and to object motion within the scene (which are treated as outliers). We use mosaicking in order to reconstruct undefined areas that result from motion compensation applied to each video frame. Registration between distant frames is performed efficiently by cascading interframe affine transformation parameters. We compare our method's performance with that of a commercial product on real-life video sequences, and show a significant improvement in stabilization quality for our method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrey Litvin, Janusz Konrad, and William Clement Karl "Probabilistic video stabilization using Kalman filtering and mosaicing", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476436
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CITATIONS
Cited by 172 scholarly publications and 1 patent.
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KEYWORDS
Video

Cameras

Motion models

Motion estimation

Affine motion model

Filtering (signal processing)

Electronic filtering

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