14,356 research outputs found
Self-correction of 3D reconstruction from multi-view stereo images
We present a self-correction approach to improving the
3D reconstruction of a multi-view 3D photogrammetry system.
The self-correction approach has been able to repair
the reconstructed 3D surface damaged by depth discontinuities.
Due to self-occlusion, multi-view range images
have to be acquired and integrated into a watertight nonredundant
mesh model in order to cover the extended surface
of an imaged object. The integrated surface often suffers
from âdentâ artifacts produced by depth discontinuities
in the multi-view range images. In this paper we propose
a novel approach to correcting the 3D integrated surface
such that the dent artifacts can be repaired automatically.
We show examples of 3D reconstruction to demonstrate the
improvement that can be achieved by the self-correction
approach. This self-correction approach can be extended
to integrate range images obtained from alternative range
capture devices
Reconstruction of Outdoor Sculptures from Silhouettes under Approximate Circular Motion of an Uncalibrated Hand-Held Camera
This paper presents a novel technique for reconstructing an outdoor sculpture from an uncalibrated image sequence acquired around it using a hand-held camera. The technique introduced here uses only the silhouettes of the sculpture for both motion estimation and model reconstruction, and no corner detection nor matching is necessary. This is very important as most sculptures are composed of smooth textureless surfaces, and hence their silhouettes are very often the only information available from their images. Besides, as opposed to previous works, the proposed technique does not require the camera motion to be perfectly circular (e.g., turntable sequence). It employs an image rectification step before the motion estimation step to obtain a rough estimate of the camera motion which is only approximately circular. A refinement process is then applied to obtain the true general motion of the camera. This allows the technique to handle large outdoor sculptures which cannot be rotated on a turntable, making it much more practical and flexible.postprin
Accelerated volumetric reconstruction from uncalibrated camera views
While both work with images, computer graphics and computer vision are inverse problems. Computer graphics starts traditionally with input geometric models and produces image sequences. Computer vision starts with input image sequences and produces geometric models. In the last few years, there has been a convergence of research to bridge the gap between the two fields.
This convergence has produced a new field called Image-based Rendering and Modeling (IBMR). IBMR represents the effort of using the geometric information recovered from real images to generate new images with the hope that the synthesized
ones appear photorealistic, as well as reducing the time spent on model creation.
In this dissertation, the capturing, geometric and photometric aspects of an IBMR system are studied. A versatile framework was developed that enables the reconstruction of scenes from images acquired with a handheld digital camera. The proposed system targets applications in areas such as Computer Gaming and Virtual Reality, from a lowcost perspective. In the spirit of IBMR, the human operator is allowed to provide the high-level information, while underlying algorithms are used to perform low-level computational work. Conforming to the latest architecture trends, we propose a streaming voxel carving method, allowing a fast GPU-based processing on commodity hardware
Structure from Motion with Higher-level Environment Representations
Computer vision is an important area focusing on understanding,
extracting and using the information from vision-based sensor. It
has many applications such as vision-based 3D reconstruction,
simultaneous localization and mapping(SLAM) and data-driven
understanding of the real world. Vision is a fundamental sensing
modality in many different fields of application.
While the traditional structure from motion mostly uses sparse
point-based feature, this thesis aims to explore the possibility
of using higher order feature representation. It starts with a
joint work which uses straight line for feature representation
and performs bundle adjustment with straight line
parameterization. Then, we further try an even higher order
representation where we use Bezier spline for parameterization.
We start with a simple case where all contours are lying on the
plane and uses Bezier splines to parametrize the curves in the
background and optimize on both camera position and Bezier
splines. For application, we present a complete end-to-end
pipeline which produces meaningful dense 3D models from natural
data of a 3D object: the target object is placed on a structured
but unknown planar background that is modeled with splines. The
data is captured using only a hand-held monocular camera.
However, this application is limited to a planar scenario and we
manage to push the parameterizations into real 3D. Following the
potential of this idea, we introduce a more flexible higher-order
extension of points that provide a general model for structural
edges in the environment, no matter if straight or curved. Our
model relies on linked B´ezier curves, the geometric intuition
of which proves great benefits during parameter initialization
and regularization. We present the
first fully automatic pipeline that is able to generate
spline-based representations without any human supervision.
Besides a full graphical formulation of the problem, we introduce
both geometric and photometric cues as well as higher-level
concepts such overall curve visibility and viewing angle
restrictions to automatically manage the correspondences in the
graph. Results prove that curve-based structure from motion with
splines is able to outperform state-of-the-art sparse
feature-based methods, as well as to model curved edges in the
environment
Content-Preserving Warps for 3D Video Stabilization
We describe a technique that transforms a video from a hand-held video camera so that it appears as if it were taken with a directed camera motion. Our method adjusts the video to appear as if it were taken from nearby viewpoints, allowing 3D camera movements to be simulated. By aiming only for perceptual plausibility, rather than accurate reconstruction, we are able to develop algorithms that can effectively recreate dynamic scenes from a single source video. Our technique first recovers the original 3D camera motion and a sparse set of 3D, static scene points using an off-the-shelf structure-frommotion system. Then, a desired camera path is computed either automatically (e.g., by fitting a linear or quadratic path) or interactively. Finally, our technique performs a least-squares optimization that computes a spatially-varying warp from each input video frame into an output frame. The warp is computed to both follow the sparse displacements suggested by the recovered 3D structure, and avoid deforming the content in the video frame. Our experiments on stabilizing challenging videos of dynamic scenes demonstrate the effectiveness of our technique
Cone carving for surface reconstruction
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