360-degree Video Stitching for Dual-fisheye Lens Cameras Based On Rigid Moving Least Squares

Dual-fisheye lens cameras are becoming popular for 360-degree video capture, especially for User-generated content (UGC), since they are affordable and portable. Images generated by the dual-fisheye cameras have limited overlap and hence require non-conventional stitching techniques to produce high-quality 360x180-degree panoramas. This paper introduces a novel method to align these images using interpolation grids based on rigid moving least squares. Furthermore, jitter is the critical issue arising when one applies the image-based stitching algorithms to video. It stems from the unconstrained movement of stitching boundary from one frame to another. Therefore, we also propose a new algorithm to maintain the temporal coherence of stitching boundary to provide jitter-free 360-degree videos. Results show that the method proposed in this paper can produce higher quality stitched images and videos than prior work.Comment: Preprint versio

Schematic of biofilm detachment mechanisms during BaSO₄ injection.

<p>Schematic of biofilm detachment mechanisms during BaSO₄ injection.</p

Information relative to the different scans and datasets used in this work as well as the corresponding details concerning the data analysis.

<p>Information relative to the different scans and datasets used in this work as well as the corresponding details concerning the data analysis.</p

Three-dimensional renderings of the solid phase (left), of the sample imaged with FeSO₄ (center) and barium suflate (right) as a contrast-enhancing agents.

<p>Three-dimensional renderings of the solid phase (left), of the sample imaged with FeSO₄ (center) and barium suflate (right) as a contrast-enhancing agents.</p

Evaluation of the presented method and another existing one for imaging biofilms in porous media.

<p>Evaluation of the presented method and another existing one for imaging biofilms in porous media.</p

Conditioned probabilities that a given phase in the FeSO4 data locally belongs to the same phase in the BaSO4 data computed for the solid (S), liquid (L) and biofilm (BF) phases for the registered Lorentz filtered FeSO₄ and BaSO₄ datasets.

<p>Conditioned probabilities that a given phase in the FeSO4 data locally belongs to the same phase in the BaSO4 data computed for the solid (S), liquid (L) and biofilm (BF) phases for the registered Lorentz filtered FeSO₄ and BaSO₄ datasets.</p

Middle slices (filtered prior to segmentation according information in Table 1) for the <i>LFeSO</i>₄ (A) and <i>BaSO</i>₄ (B) datasets.

<p>The corresponding 8 bit gray value histograms are shown in C) for the <i>BaSO</i>₄ (blue) dataset and for the <i>LFeSO</i>₄ (red) dataset after contrast enhancement and application of the 3D curvature-driven diffusive filter. For the <i>LFeSO</i>₄ dataset, the vertical dashed lines in yellow, purple and green correspond to isosurface values of 64, 73 and 82 used for the segmentation and the corresponding sensitivity analysis. The peaks corresponding to the different phases are annotated. (D) and (E) show the segmented datasets where the solid, liquid and biofilm phases are color coded in white, blue and green respectively. The scale bar represents 1 mm.</p

Profiles of the volumetric fractions (S: solid, L: liquid, BF: biofilm) obtained for the different datasets (BaSO₄: small dashes, FeSO₄: longer dashes).

<p>The shaded region is defined by the results obtained for the threshold sensitivity analysis. For the sake of clarity, the results of this sensitivity analysis are not added to the liquid phases. The average volumetric fractions (in percent) for the different phases (Solid <i>V</i>_<i>S</i>, Liquid <i>V</i>_<i>L</i>, Biofilm <i>V</i>_<i>BF</i>) obtained with the two different contrast-enhancing agents is given in the legend.</p