Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment

This paper presents a novel algorithm that utilizes a 2D floorplan to align panorama RGBD scans. While effective panorama RGBD alignment techniques exist, such a system requires extremely dense RGBD image sampling. Our approach can significantly reduce the number of necessary scans with the aid of a floorplan image. We formulate a novel Markov Random Field inference problem as a scan placement over the floorplan, as opposed to the conventional scan-to-scan alignment. The technical contributions lie in multi-modal image correspondence cues (between scans and schematic floorplan) as well as a novel coverage potential avoiding an inherent stacking bias. The proposed approach has been evaluated on five challenging large indoor spaces. To the best of our knowledge, we present the first effective system that utilizes a 2D floorplan image for building-scale 3D pointcloud alignment. The source code and the data will be shared with the community to further enhance indoor mapping research

Optical Image Blending for Underwater Mosaics

Typical problems for creation of consistent underwater mosaic are misalignment and inhomogeneous illumination of the image frames, which causes visible seams and consequently complicates post-processing of the mosaics such as object recognition and shape extraction. Two recently developed image blending methods were explored in the literature: gradient domain stitching and graph-cut method, and they allow for improvement of illumination inconsistency and ghosting effects, respectively. However, due to the specifics of underwater imagery, these two methods cannot be used within a straightforward manner. In this paper, a new improved blending algorithm is proposed based on these two methods. By comparing with the previous methods from a perceptual point of view and as a potential input for pattern recognition algorithms, our results show an improvement in decreasing the mosaic degradation due to feature doubling and rapid illumination change