602 research outputs found
Convex Relaxations of SE(2) and SE(3) for Visual Pose Estimation
This paper proposes a new method for rigid body pose estimation based on
spectrahedral representations of the tautological orbitopes of and
. The approach can use dense point cloud data from stereo vision or an
RGB-D sensor (such as the Microsoft Kinect), as well as visual appearance data.
The method is a convex relaxation of the classical pose estimation problem, and
is based on explicit linear matrix inequality (LMI) representations for the
convex hulls of and . Given these representations, the relaxed
pose estimation problem can be framed as a robust least squares problem with
the optimization variable constrained to these convex sets. Although this
formulation is a relaxation of the original problem, numerical experiments
indicate that it is indeed exact - i.e. its solution is a member of or
- in many interesting settings. We additionally show that this method
is guaranteed to be exact for a large class of pose estimation problems.Comment: ICRA 2014 Preprin
Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees
This paper addresses the problem of ad hoc microphone array calibration where
only partial information about the distances between microphones is available.
We construct a matrix consisting of the pairwise distances and propose to
estimate the missing entries based on a novel Euclidean distance matrix
completion algorithm by alternative low-rank matrix completion and projection
onto the Euclidean distance space. This approach confines the recovered matrix
to the EDM cone at each iteration of the matrix completion algorithm. The
theoretical guarantees of the calibration performance are obtained considering
the random and locally structured missing entries as well as the measurement
noise on the known distances. This study elucidates the links between the
calibration error and the number of microphones along with the noise level and
the ratio of missing distances. Thorough experiments on real data recordings
and simulated setups are conducted to demonstrate these theoretical insights. A
significant improvement is achieved by the proposed Euclidean distance matrix
completion algorithm over the state-of-the-art techniques for ad hoc microphone
array calibration.Comment: In Press, available online, August 1, 2014.
http://www.sciencedirect.com/science/article/pii/S0165168414003508, Signal
Processing, 201
Computational limitations of model based recognition
Includes bibliographical references (p. 13-14).Cover title.Research supported by the U.S. Army Research Office. DAAL03-86-K-0171 Research supported by the Office of Naval Research under an Air Force Contract. F196128-90-C-0002Haim Shvaytser (Schweitzer), Sanjeev R. Kulkarni
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
The implicit objective of the biennial "international - Traveling Workshop on
Interactions between Sparse models and Technology" (iTWIST) is to foster
collaboration between international scientific teams by disseminating ideas
through both specific oral/poster presentations and free discussions. For its
second edition, the iTWIST workshop took place in the medieval and picturesque
town of Namur in Belgium, from Wednesday August 27th till Friday August 29th,
2014. The workshop was conveniently located in "The Arsenal" building within
walking distance of both hotels and town center. iTWIST'14 has gathered about
70 international participants and has featured 9 invited talks, 10 oral
presentations, and 14 posters on the following themes, all related to the
theory, application and generalization of the "sparsity paradigm":
Sparsity-driven data sensing and processing; Union of low dimensional
subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph
sensing/processing; Blind inverse problems and dictionary learning; Sparsity
and computational neuroscience; Information theory, geometry and randomness;
Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?;
Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website:
http://sites.google.com/site/itwist1
OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM
In this work, we explore the use of objects in Simultaneous Localization and
Mapping in unseen worlds and propose an object-aided system (OA-SLAM). More
precisely, we show that, compared to low-level points, the major benefit of
objects lies in their higher-level semantic and discriminating power. Points,
on the contrary, have a better spatial localization accuracy than the generic
coarse models used to represent objects (cuboid or ellipsoid). We show that
combining points and objects is of great interest to address the problem of
camera pose recovery. Our main contributions are: (1) we improve the
relocalization ability of a SLAM system using high-level object landmarks; (2)
we build an automatic system, capable of identifying, tracking and
reconstructing objects with 3D ellipsoids; (3) we show that object-based
localization can be used to reinitialize or resume camera tracking. Our fully
automatic system allows on-the-fly object mapping and enhanced pose tracking
recovery, which we think, can significantly benefit to the AR community. Our
experiments show that the camera can be relocalized from viewpoints where
classical methods fail. We demonstrate that this localization allows a SLAM
system to continue working despite a tracking loss, which can happen frequently
with an uninitiated user. Our code and test data are released at
gitlab.inria.fr/tangram/oa-slam.Comment: ISMAR 202
Stable Camera Motion Estimation Using Convex Programming
We study the inverse problem of estimating n locations (up to
global scale, translation and negation) in from noisy measurements of a
subset of the (unsigned) pairwise lines that connect them, that is, from noisy
measurements of for some pairs (i,j) (where the
signs are unknown). This problem is at the core of the structure from motion
(SfM) problem in computer vision, where the 's represent camera locations
in . The noiseless version of the problem, with exact line measurements,
has been considered previously under the general title of parallel rigidity
theory, mainly in order to characterize the conditions for unique realization
of locations. For noisy pairwise line measurements, current methods tend to
produce spurious solutions that are clustered around a few locations. This
sensitivity of the location estimates is a well-known problem in SfM,
especially for large, irregular collections of images.
In this paper we introduce a semidefinite programming (SDP) formulation,
specially tailored to overcome the clustering phenomenon. We further identify
the implications of parallel rigidity theory for the location estimation
problem to be well-posed, and prove exact (in the noiseless case) and stable
location recovery results. We also formulate an alternating direction method to
solve the resulting semidefinite program, and provide a distributed version of
our formulation for large numbers of locations. Specifically for the camera
location estimation problem, we formulate a pairwise line estimation method
based on robust camera orientation and subspace estimation. Lastly, we
demonstrate the utility of our algorithm through experiments on real images.Comment: 40 pages, 12 figures, 6 tables; notation and some unclear parts
updated, some typos correcte
NMDA-based pattern discrimination in a modeled cortical neuron
Compartmental simulations of an anatomically characterized cortical pyramidal cell were carried out to study the integrative behavior of a complex dendritic tree. Previous theoretical (Feldman and Ballard 1982; Durbin and Rumelhart 1989; Mel 1990; Mel and Koch 1990; Poggio and Girosi 1990) and compartmental modeling (Koch et al. 1983; Shepherd et al. 1985; Koch and Poggio 1987; Rall and Segev 1987; Shepherd and Brayton 1987; Shepherd et al. 1989; Brown et al. 1991) work had suggested that multiplicative interactions among groups of neighboring synapses could greatly enhance the processing power of a neuron relative to a unit with only a single global firing threshold. This issue was investigated here, with a particular focus on the role of voltage-dependent N-methyl-D-asparate (NMDA) channels in the generation of cell responses. First, it was found that when a large proportion of the excitatory synaptic input to dendritic spines is carried by NMDA channels, the pyramidal cell responds preferentially to spatially clustered, rather than random, distributions of activated synapses. Second, based on this mechanism, the NMDA-rich neuron is shown to be capable of solving a nonlinear pattern discrimination task. We propose that manipulation of the spatial ordering of afferent synaptic connections onto the dendritic arbor is a possible biological strategy for pattern information storage during learning
Robust and affordable localization and mapping for 3D reconstruction. Application to architecture and construction
La localización y mapeado simultáneo a partir de una sola cámara en movimiento se conoce como Monocular
SLAM. En esta tesis se aborda este problema con cámaras de bajo coste cuyo principal reto consiste en ser
robustos al ruido, blurring y otros artefactos que afectan a la imagen. La aproximación al problema es discreta,
utilizando solo puntos de la imagen significativos para localizar la cámara y mapear el entorno. La principal
contribución es una simplificación del grafo de poses que permite mejorar la precisión en las escenas más
habituales, evaluada de forma exhaustiva en 4 datasets. Los resultados del mapeado permiten obtener una
reconstrucción 3D de la escena que puede ser utilizada en arquitectura y construcción para Modelar la Información
del Edificio (BIM). En la segunda parte de la tesis proponemos incorporar dicha información en un sistema de
visualización avanzada usando WebGL que ayude a simplificar la implantación de la metodologÃa BIM.Departamento de Informática (Arquitectura y TecnologÃa de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Doctorado en Informátic
- …