Spatial and Temporal Interpolation of Multi-view Image Sequences [chapter]

Tobias Gurdan, Martin R. Oswald, Daniel Gurdan, Daniel Cremers
2014 Lecture Notes in Computer Science  
We propose a simple and effective framework for multi-view image sequence interpolation in space and time. For spatial view point interpolation we present a robust feature-based matching algorithm that allows for wide-baseline camera configurations. To this end, we introduce two novel filtering approaches for outlier elimination and a robust approach for match extrapolations at the image boundaries. For smallbaseline and temporal interpolations we rely on an established optical flow based
more » ... ch. We perform a quantitative and qualitative evaluation of our framework and present applications and results. Our method has a low runtime and results can compete with state-of-the-art methods. Fig. 1 : Spatial view point interpolation between two images. Our approach robustly handles wide-baseline view point interpolations. From left to right: source image, interpolation at t = 1/3, interpolation at t = 2/3, target image.
doi:10.1007/978-3-319-11752-2_24 fatcat:oguvp3xxivda7jsz5tkheiydea