1,727 research outputs found
3D Reconstruction with Low Resolution, Small Baseline and High Radial Distortion Stereo Images
In this paper we analyze and compare approaches for 3D reconstruction from
low-resolution (250x250), high radial distortion stereo images, which are
acquired with small baseline (approximately 1mm). These images are acquired
with the system NanEye Stereo manufactured by CMOSIS/AWAIBA. These stereo
cameras have also small apertures, which means that high levels of illumination
are required. The goal was to develop an approach yielding accurate
reconstructions, with a low computational cost, i.e., avoiding non-linear
numerical optimization algorithms. In particular we focused on the analysis and
comparison of radial distortion models. To perform the analysis and comparison,
we defined a baseline method based on available software and methods, such as
the Bouguet toolbox [2] or the Computer Vision Toolbox from Matlab. The
approaches tested were based on the use of the polynomial model of radial
distortion, and on the application of the division model. The issue of the
center of distortion was also addressed within the framework of the application
of the division model. We concluded that the division model with a single
radial distortion parameter has limitations
3D Reconstruction with Low Resolution, Small Baseline and High Radial Distortion Stereo Images
In this paper we analyze and compare approaches for 3D reconstruction from
low-resolution (250x250), high radial distortion stereo images, which are
acquired with small baseline (approximately 1mm). These images are acquired
with the system NanEye Stereo manufactured by CMOSIS/AWAIBA. These stereo
cameras have also small apertures, which means that high levels of illumination
are required. The goal was to develop an approach yielding accurate
reconstructions, with a low computational cost, i.e., avoiding non-linear
numerical optimization algorithms. In particular we focused on the analysis and
comparison of radial distortion models. To perform the analysis and comparison,
we defined a baseline method based on available software and methods, such as
the Bouguet toolbox [2] or the Computer Vision Toolbox from Matlab. The
approaches tested were based on the use of the polynomial model of radial
distortion, and on the application of the division model. The issue of the
center of distortion was also addressed within the framework of the application
of the division model. We concluded that the division model with a single
radial distortion parameter has limitations
Creating virtual models from uncalibrated camera views
The reconstruction of photorealistic 3D models from camera views is becoming an ubiquitous element in many applications that simulate physical interaction with the real world. In this paper, we present a low-cost, interactive pipeline aimed at non-expert users, that achieves 3D reconstruction from multiple views acquired with a standard digital camera. 3D models are amenable to access through diverse representation modalities that typically imply trade-offs between level of detail, interaction, and computational costs. Our approach allows users to selectively control the complexity of different surface regions, while requiring only simple 2D image editing operations. An initial reconstruction at coarse resolution is followed by an iterative refining of the surface areas corresponding to the selected regions
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs
Human visual system relies on both binocular stereo cues and monocular
focusness cues to gain effective 3D perception. In computer vision, the two
problems are traditionally solved in separate tracks. In this paper, we present
a unified learning-based technique that simultaneously uses both types of cues
for depth inference. Specifically, we use a pair of focal stacks as input to
emulate human perception. We first construct a comprehensive focal stack
training dataset synthesized by depth-guided light field rendering. We then
construct three individual networks: a Focus-Net to extract depth from a single
focal stack, a EDoF-Net to obtain the extended depth of field (EDoF) image from
the focal stack, and a Stereo-Net to conduct stereo matching. We show how to
integrate them into a unified BDfF-Net to obtain high-quality depth maps.
Comprehensive experiments show that our approach outperforms the
state-of-the-art in both accuracy and speed and effectively emulates human
vision systems
Cross-calibration of Time-of-flight and Colour Cameras
Time-of-flight cameras provide depth information, which is complementary to
the photometric appearance of the scene in ordinary images. It is desirable to
merge the depth and colour information, in order to obtain a coherent scene
representation. However, the individual cameras will have different viewpoints,
resolutions and fields of view, which means that they must be mutually
calibrated. This paper presents a geometric framework for this multi-view and
multi-modal calibration problem. It is shown that three-dimensional projective
transformations can be used to align depth and parallax-based representations
of the scene, with or without Euclidean reconstruction. A new evaluation
procedure is also developed; this allows the reprojection error to be
decomposed into calibration and sensor-dependent components. The complete
approach is demonstrated on a network of three time-of-flight and six colour
cameras. The applications of such a system, to a range of automatic
scene-interpretation problems, are discussed.Comment: 18 pages, 12 figures, 3 table
Self-calibration and motion recovery from silhouettes with two mirrors
LNCS v. 7724-7727 (pts. 1-4) entitled: Computer vision - ACCV 2012: 11th Asian Conference on Computer Vision ... 2012: revised selected papersThis paper addresses the problem of self-calibration and motion recovery from a single snapshot obtained under a setting of two mirrors. The mirrors are able to show five views of an object in one image. In this paper, the epipoles of the real and virtual cameras are firstly estimated from the intersection of the bitangent lines between corresponding images, from which we can easily derive the horizon of the camera plane. The imaged circular points and the angle between the mirrors can then be obtained from equal angles between the bitangent lines, by planar rectification. The silhouettes produced by reflections can be treated as a special circular motion sequence. With this observation, technique developed for calibrating a circular motion sequence can be exploited to simplify the calibration of a single-view two-mirror system. Different from the state-of-the-art approaches, only one snapshot is required in this work for self-calibrating a natural camera and recovering the poses of the two mirrors. This is more flexible than previous approaches which require at least two images. When more than a single image is available, each image can be calibrated independently and the problem of varying focal length does not complicate the calibration problem. After the calibration, the visual hull of the objects can be obtained from the silhouettes. Experimental results show the feasibility and the preciseness of the proposed approach. © 2013 Springer-Verlag.postprin
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