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Found 12 papers, 4 papers with code
Uncertainty Propagation and Bayesian Fusion on Unimodular Lie Groups from a Parametric Perspective
We address the problem of uncertainty propagation and Bayesian fusion on unimodular Lie groups.
Uncertainty Propagation on Unimodular Matrix Lie Groups
This paper addresses uncertainty propagation on unimodular matrix Lie groups that have a surjective exponential map.
A Lie-Theoretic Approach to Propagating Uncertainty Jointly in Attitude and Angular Momentum
Dynamic state estimation, as opposed to kinematic state estimation, seeks to estimate not only the orientation of a rigid body but also its angular velocity, through Euler's equations of rotational motion.
Marching-Primitives: Shape Abstraction from Signed Distance Function
Representing complex objects with basic geometric primitives has long been a topic in computer vision.
Primitive-based Shape Abstraction via Nonparametric Bayesian Inference
In this paper, we propose a novel non-parametric Bayesian statistical method to infer an abstraction, consisting of an unknown number of geometric primitives, from a point cloud.
Robust and Accurate Superquadric Recovery: a Probabilistic Approach
Among geometric primitives, superquadrics are well known for their ability to represent a wide range of shapes with few parameters.
Can I Pour into It? Robot Imagining Open Containability Affordance of Previously Unseen Objects via Physical Simulations
In this letter, we propose a novel method for robots to "imagine" the open containability affordance of a previously unseen object via physical simulations.
Is That a Chair? Imagining Affordances Using Simulations of an Articulated Human Body
In our method, the robot "imagines" the affordance of an arbitrarily oriented object as a chair by simulating a physical sitting interaction between an articulated human body and the object.
Curvature: A signature for Action Recognition in Video Sequences
In this paper, a novel signature of human action recognition, namely the curvature of a video sequence, is introduced.
Quotienting Impertinent Camera Kinematics for 3D Video Stabilization
The foundation of this approach is a novel camera motion model that allows for real-world camera poses to be recovered directly from 3D motion fields.
Signal Alignment for Humanoid Skeletons via the Globally Optimal Reparameterization Algorithm
Here, we introduce a variant of GORA for humanoid action recognition with skeleton sequences, which we call GORA-S. We briefly review the algorithm's mathematical foundations and contextualize them in the problem of action recognition with skeleton sequences.
The Globally Optimal Reparameterization Algorithm: an Alternative to Fast Dynamic Time Warping for Action Recognition in Video Sequences
We compare the performance of GORA with that of the DTW and FastDTW algorithms, in terms of computational efficiency and accuracy in matching signals.
