Capturing Panoramic Depth Images with a Single Standard Camera

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera’s optical center from the rotational center of the system we are able to capture the motion parallax effect which enables the stereo reconstruction. The camera is rotating on a circular path with the step defined by an angle equivalent to one column of the captured image. The equation for depth estimation can be easily extracted from system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. We focused mainly on the system analysis. The system performs well in the reconstruction of small indoor spaces

Image-Based Scene Representations for Head-Motion Parallax in 360° Panoramas

Creation and delivery of “RealVR” experiences essentially consists of the following four main steps: capture, processing, representation and rendering. In this chapter, we present, compare, and discuss two recent end-to-end approaches, Parallax360 by Luo et al. [9] and MegaParallax by Bertel et al. [3]. Both propose complete pipelines for RealVR content generation and novel-view synthesis with head-motion parallax for 360° environments.Parallax360 uses a robotic arm for capturing thousands of input views on the surface of a sphere. Based on precomputed disparity motion fields and pairwise optical flow, novel viewpoints are synthesized on the fly using flow-based blending of the nearest two to three input views which provides compelling head-motion parallax.MegaParallax proposes a pipeline for RealVR content generation and rendering that emphasizes casual, hand-held capturing. The approach introduces view-dependent flow-based blending to enable novel-view synthesis with head-motion parallax within a viewing area determined by the field of view of the input cameras and the capturing radius.We describe both methods and discuss their similarities and differences in corresponding steps in the RealVR pipeline and show selected results. The chapter ends by discussing advantages and disadvantages as well as outlining the most important limitations and future work.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 66599

Unsupervised three-dimensional reconstruction of small rocks from a single two-dimensional image

Surfaces covered with pebbles and small rocks can often be found in nature or in human shaped environments. Generating an accurate three-dimensional model of those kind of surfaces from a reference image can be challenging, especially if one wants to be able to animate each pebble individually. To undertake this kind of job manually is time consuming and impossible to achieve in dynamic terrains animations. The method described in this paper allows unsupervised automatic generation of three-dimensional textured rocks from a two-dimensional image aiming to closely match the original image as much as possible

Panoramic Depth Imaging: Single Standard Camera Approach

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera’s optical center from the rotational center of the system we are able to capture the motion parallax effect which enables stereo reconstruction. The camera is rotating on a circular path with a step defined by the angle, equivalent to one pixel column of the captured image. The equation for depth estimation can be easily extracted from the system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric pixel columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. The search space on the epipolar line can be additionaly constrained. The focus of the paper is mainly on the system analysis. Results of the stereo reconstruction procedure and quality evaluation of generated depth images are quite promissing. The system performs well for reconstruction of small indoor spaces. Our finall goal is to develop a system for automatic navigation of a mobile robot in a room

Virtual viewpoint three-dimensional panorama

Conventional panoramic images are known to provide for an enhanced field of view in which the scene always has a fixed appearance. The idea presented in this paper focuses on the use of the concept of virtual viewpoint creation to generate different panoramic images of the same scene with three-dimensional component. Three-dimensional effect in a resultant panorama is realized by superimposing a stereo-pair of panoramic images

Mosaiced-Based Panoramic Depth Imaging with a Single Standard Camera

In this article we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera’s optical center from the rotational center of the system we are able to capture the motion parallax effect which enables the stereo reconstruction. The camera is rotating on a circular path with the step defined by an angle, equivalent to one column of the captured image. The equation for depth estimation can be easily extracted from system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. We focused mainly on the system analysis. Results of the stereo reconstruction procedure and quality evaluation of generated depth images are quite promissing. The system performs well in the reconstruction of small indoor spaces. Our finall goal is to develop a system for automatic navigation of a mobile robot in a room