Search Results for author:
Found 9 papers, 1 papers with code
GISR: Geometric Initialization and Silhouette-based Refinement for Single-View Robot Pose and Configuration Estimation
For autonomous robotics applications, it is crucial that robots are able to accurately measure their potential state and perceive their environment, including other agents within it (e. g., cobots interacting with humans).
GenDepth: Generalizing Monocular Depth Estimation for Arbitrary Camera Parameters via Ground Plane Embedding
Learning-based monocular depth estimation leverages geometric priors present in the training data to enable metric depth perception from a single image, a traditionally ill-posed problem.
A Distance-Geometric Method for Recovering Robot Joint Angles From an RGB Image
Autonomous manipulation systems operating in domains where human intervention is difficult or impossible (e. g., underwater, extraterrestrial or hazardous environments) require a high degree of robustness to sensing and communication failures.
Recalibrating the KITTI Dataset Camera Setup for Improved Odometry Accuracy
In this paper, we propose a new approach for one shot calibration of the KITTI dataset multiple camera setup.
Feature-based Event Stereo Visual Odometry
We compared our method to the ESVO method, which is the first and still the only stereo event odometry method, showing on par performance on the MVSEC sequences, while on the DSEC dataset ESVO, unlike our method, was unable to handle outdoor driving scenario with default parameters.
Ensemble of LSTMs and feature selection for human action prediction
We have thoroughly analyzed the MoGaze dataset and selected a reduced set of cues for this task.
Robotics
Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors
In this paper, we propose a novel method for event lifetime estimation of stereo event-cameras, allowing generation of sharp gradient images of events that serve as input to disparity estimation methods.
Pedestrian Tracking by Probabilistic Data Association and Correspondence Embeddings
We investigate tracking-by-detection approaches based on a deep learning detector, joint integrated probabilistic data association (JIPDA), and appearance-based tracking of deep correspondence embeddings.
Global Localization Based on 3D Planar Surface Segments
Global localization of a mobile robot using planar surface segments extracted from depth images is considered.
