Mosaic-based panoramic depth imaging with a single standard camera (original) (raw)

Panoramic depth imaging: Single standard camera approach

International Journal of Computer Vision, 2002

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.

Capturing mosaic-based panoramic depth images with a single standard camera

2001

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.

Multiperspective panoramic depth imaging

Computer vision and robotics, 2006

In this chapter we present a stereo panoramic depth imaging system, which builds depth panoramas from multiperspective panoramas while using only one standard camera.

Towards a real time panoramic depth sensor

Computer Analysis of Images and Patterns, 2003

Recently we have presented a system for panoramic depth imaging with a single standard camera. One of the problems of such a system is the fact that we cannot generate a stereo pair of images in real time. This paper presents a possible solution to this problem. Based on a new sensor setup simulations were performed to establish the quality of new results in comparison to results obtained with the old sensor setup. The goal of the paper is to reveal whether the new setup can be used for real time capturing of panoramic depth images and consequently for autonomous navigation of a mobile robot in a room.

Panoramic depth imaging with a single standard camera

IEEE International Symposium on Intelligent Signal Processing, 2001

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 an offset 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.

Panoramic Stereovision and Scene Reconstruction

2016

With advancement of research in robotics and computer vision, an increasingly high number of applications require the understanding of a scene in three dimensions. A variety of systems are deployed to do the same. This thesis explores a novel 3D imaging technique. This involves the use of catadioptric cameras in a stereoscopic arrangement. A secondary system aims to stabilize the system in the event that the cameras are misaligned during operation. The system provides a stark advantage due to it being a cost effective alternative to present day standard state-of-the-art systems that achieve the same goal of 3D imaging. The compromise lies in the quality of depth estimation, which can be overcome with a different imager and calibration. The result was a panoramic disparity map generated by the system.

A Computer Vision Sensor for Panoramic Depth Perception

Lecture Notes in Computer Science, 2005

A practical way for obtaining depth in computer vision is the use of structured light systems. For panoramic depth reconstruction several images are needed which most likely implies the construction of a sensor with mobile elements. Moreover, misalignments can appear for non-static scenes. Omnidirectional cameras offer a much wider field of view than the perspective ones, capture a panoramic image at every moment and alleviate the problems due to occlusions. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to obtain panoramic depth information. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector.

Analysis and Design of Panoramic Stereo Vision Using EquiAngular Pixel Cameras

1999

In this report we discuss methods to perform stereo vision using a novel configuration of devices that allow imaging of a very wide field of view (full 360 degrees in the azimuth and up to 120 degrees in elevation). Since the wide field of view produces signficant distortion that varies with viewpoint, we have developed a method to do correlation matching and triangulation for stereo vision that incorporates mirror shape. In this report we evaluate various configurations of cameras and mirrors that could be used to produce stereo imagery, including one that can use a single camera to produce stereo images. Range from panoramic stereo imagery can be used in many applications that require the three dimensional shape of the world. The chief advantages of this method is that it can made cheaply with no moving parts and can provide dense range data. Specifically, this kind of a sensor could be used for telepresence, autonomous navigation by robots, automatic mapping of environments and attitude estimation.

A method for panoramic stereo image acquisition

One of the key technologies for one-to-many visual communication is panoramic stereo, in which stereoscopic images for arbitrary horizontal directions are presented to multiple users, according to their positions and postures. In this paper, one of the methods for capturing panoramic stereo motion pictures is proposed and evaluated, along with an experimentation. Through preliminary experimentation, we have confirmed the effectiveness of methods using a curved mirror.

A Panoramic 3D Reconstruction System Based on the Projection of Patterns

International Journal of Advanced Robotic Systems, 2014

This work presents the implementation of a 3D reconstruction system capable of reconstructing a 360-degree scene with a single acquisition using a projection of patterns. The system is formed by two modules: the first module is a CCD camera with a parabolic mirror that allows the acquisition of catadioptric images. The second module consists of a light projector and a parabolic mirror that is used to generate the pattern projections over the object that will be reconstructed. The projection system has a 360-degree field of view and both modules were calibrated to obtain the extrinsic parameters. To validate the functionality of the system, we performed 3D reconstructions of three objects, and show the reconstruction error analysis.