Search Results for author:
Found 7 papers, 2 papers with code
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.
Put the Bear on the Chair! Intelligent Robot Interaction with Previously Unseen Chairs via Robot Imagination
Results show that our method enables the robot to autonomously seat the teddy bear on the 12 previously unseen chairs with a very high success rate.
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.
