Unsteady camera zoom stabilization using slope estimation over interest warping vectors

• Warping singularity elimination using local optima based interest warping vector.
• New zoom estimation approach using slope evaluation of projection warping vectors.
• Image-centered zoom extended to arbitrary point using residual vector translation.
• Improved range of zoom factor achieved over existing projection based technique.
• Improved accuracy under blur, intensity variation and noise as textural artifacts.

Projections being based on global image representative are considered as simplified and efficient stabilization solutions under poor textural or imaging conditions. The existing projection algorithms are investigated only for translation or rotation stabilization, but the image captured with unsteady camera also suffers from undesired zoom-in/out effect. This paper presents a new zoom estimation algorithm for extended projection applicability. Camera focusing generally being effective around its optical axis, produces zooming around the image center. This image-centered zoom results in an opposite relative motion (stretching/compression) in two halves of the image projections. A novel concept of utilizing this relative longitudinal projection motion is proposed for camera zoom estimation. Derivative dynamic time warping is used for image projection alignment and the effect of mismatched-warping singularities leading to motion estimation error is removed by selecting some key warping vectors labeled as Interest Warping Vectors. Slope values of these interest warping vectors in the two projection-halves are utilized for zoom factor estimation and the approach is also generalized for arbitrary zoom-center under forward translation. Robustness of the proposed algorithm tested with artificial textural artifacts is verified with motion accuracy analysis on various sequentially zoomed test and real-world images within 0.8 to 1.2 scale factor range.