12,417 research outputs found
Mesh-based 3D Textured Urban Mapping
In the era of autonomous driving, urban mapping represents a core step to let
vehicles interact with the urban context. Successful mapping algorithms have
been proposed in the last decade building the map leveraging on data from a
single sensor. The focus of the system presented in this paper is twofold: the
joint estimation of a 3D map from lidar data and images, based on a 3D mesh,
and its texturing. Indeed, even if most surveying vehicles for mapping are
endowed by cameras and lidar, existing mapping algorithms usually rely on
either images or lidar data; moreover both image-based and lidar-based systems
often represent the map as a point cloud, while a continuous textured mesh
representation would be useful for visualization and navigation purposes. In
the proposed framework, we join the accuracy of the 3D lidar data, and the
dense information and appearance carried by the images, in estimating a
visibility consistent map upon the lidar measurements, and refining it
photometrically through the acquired images. We evaluate the proposed framework
against the KITTI dataset and we show the performance improvement with respect
to two state of the art urban mapping algorithms, and two widely used surface
reconstruction algorithms in Computer Graphics.Comment: accepted at iros 201
A Stochastic Approach to Shortcut Bridging in Programmable Matter
In a self-organizing particle system, an abstraction of programmable matter,
simple computational elements called particles with limited memory and
communication self-organize to solve system-wide problems of movement,
coordination, and configuration. In this paper, we consider a stochastic,
distributed, local, asynchronous algorithm for "shortcut bridging", in which
particles self-assemble bridges over gaps that simultaneously balance
minimizing the length and cost of the bridge. Army ants of the genus Eciton
have been observed exhibiting a similar behavior in their foraging trails,
dynamically adjusting their bridges to satisfy an efficiency trade-off using
local interactions. Using techniques from Markov chain analysis, we rigorously
analyze our algorithm, show it achieves a near-optimal balance between the
competing factors of path length and bridge cost, and prove that it exhibits a
dependence on the angle of the gap being "shortcut" similar to that of the ant
bridges. We also present simulation results that qualitatively compare our
algorithm with the army ant bridging behavior. Our work gives a plausible
explanation of how convergence to globally optimal configurations can be
achieved via local interactions by simple organisms (e.g., ants) with some
limited computational power and access to random bits. The proposed algorithm
also demonstrates the robustness of the stochastic approach to algorithms for
programmable matter, as it is a surprisingly simple extension of our previous
stochastic algorithm for compression.Comment: Published in Proc. of DNA23: DNA Computing and Molecular Programming
- 23rd International Conference, 2017. An updated journal version will appear
in the DNA23 Special Issue of Natural Computin
Hexagonal structure for intelligent vision
Using hexagonal grids to represent digital images have been studied for more than 40 years. Increased processing capabilities of graphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications and brought new interests on this topic. The hexagonal structure is considered to be preferable to the rectangular structure due to its higher sampling efficiency, consistent connectivity and higher angular resolution and is even proved to be superior to square structure in many applications. Since there is no mature hardware for hexagonal-based image capture and display, square to hexagonal image conversion has to be done before hexagonal-based image processing. Although hexagonal image representation and storage has not yet come to a standard, experiments based on existing hexagonal coordinate systems have never ceased. In this paper, we firstly introduced general reasons that hexagonally sampled images are chosen for research. Then, typical hexagonal coordinates and addressing schemes, as well as hexagonal based image processing and applications, are fully reviewed. © 2005 IEEE
Plane-Based Optimization of Geometry and Texture for RGB-D Reconstruction of Indoor Scenes
We present a novel approach to reconstruct RGB-D indoor scene with plane
primitives. Our approach takes as input a RGB-D sequence and a dense coarse
mesh reconstructed by some 3D reconstruction method on the sequence, and
generate a lightweight, low-polygonal mesh with clear face textures and sharp
features without losing geometry details from the original scene. To achieve
this, we firstly partition the input mesh with plane primitives, simplify it
into a lightweight mesh next, then optimize plane parameters, camera poses and
texture colors to maximize the photometric consistency across frames, and
finally optimize mesh geometry to maximize consistency between geometry and
planes. Compared to existing planar reconstruction methods which only cover
large planar regions in the scene, our method builds the entire scene by
adaptive planes without losing geometry details and preserves sharp features in
the final mesh. We demonstrate the effectiveness of our approach by applying it
onto several RGB-D scans and comparing it to other state-of-the-art
reconstruction methods.Comment: in International Conference on 3D Vision 2018; Models and Code: see
https://github.com/chaowang15/plane-opt-rgbd. arXiv admin note: text overlap
with arXiv:1905.0885
Dictionary Learning-based Inpainting on Triangular Meshes
The problem of inpainting consists of filling missing or damaged regions in
images and videos in such a way that the filling pattern does not produce
artifacts that deviate from the original data. In addition to restoring the
missing data, the inpainting technique can also be used to remove undesired
objects. In this work, we address the problem of inpainting on surfaces through
a new method based on dictionary learning and sparse coding. Our method learns
the dictionary through the subdivision of the mesh into patches and rebuilds
the mesh via a method of reconstruction inspired by the Non-local Means method
on the computed sparse codes. One of the advantages of our method is that it is
capable of filling the missing regions and simultaneously removes noise and
enhances important features of the mesh. Moreover, the inpainting result is
globally coherent as the representation based on the dictionaries captures all
the geometric information in the transformed domain. We present two variations
of the method: a direct one, in which the model is reconstructed and restored
directly from the representation in the transformed domain and a second one,
adaptive, in which the missing regions are recreated iteratively through the
successive propagation of the sparse code computed in the hole boundaries,
which guides the local reconstructions. The second method produces better
results for large regions because the sparse codes of the patches are adapted
according to the sparse codes of the boundary patches. Finally, we present and
analyze experimental results that demonstrate the performance of our method
compared to the literature
Self-Replication and Self-Assembly for Manufacturing
It has been argued that a central objective of nanotechnology is to make
products inexpensively, and that self-replication is an effective approach
to very low-cost manufacturing. The research presented here is intended to
be a step towards this vision. We describe a computational simulation of
nanoscale machines floating in a virtual liquid. The machines can bond
together to form strands (chains) that self-replicate and self-assemble
into user-specified meshes. There are four types of machines and the
sequence of machine types in a strand determines the shape of the mesh
they will build. A strand may be in an unfolded state, in which the bonds
are straight, or in a folded state, in which the bond angles depend on the
types of machines. By choosing the sequence of machine types in a strand,
the user can specify a variety of polygonal shapes. A simulation typically
begins with an initial unfolded seed strand in a soup of unbonded machines.
The seed strand replicates by bonding with free machines in the soup. The
child strands fold into the encoded polygonal shape, and then the polygons
drift together and bond to form a mesh. We demonstrate that a variety of
polygonal meshes can be manufactured in the simulation, by simply changing
the sequence of machine types in the seed
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