← Search

Alen Alempijevic

9 accepted papers

2023

Semantic Keypoint Extraction for Scanned Animals using Multi-Depth-Camera Systems

ICRA 2023poster

Keypoint annotation in pointclouds is an important task for 3D reconstruction, object tracking and alignment, in particular in deformable or moving scenes. In the context of agriculture robotics, it is a critical task for livestock automation to work toward condition assessment or behaviour recognit…

Cited by 8SourcecodeScholar
2023

Skirting Line Estimation Using Sparse to Dense Deformation

IROS 2023poster

Automating the process of fleece contaminant removal has the potential to drastically improve the quality of wool leaving the farm gate. Towards this goal, we present a method to automatically extract skirting lines, i.e., the separations between clean and contaminated wool of a fleece using RGB ima…

Cited by 2SourceScholar
2022

Constrained Gaussian Processes With Integrated Kernels for Long-Horizon Prediction of Dense Pedestrian Crowd Flows

RA-L 2022

In this letter, we present a novel approach for predicting pedestrian crowd dynamics over longer time horizons (30 s). In dense environments over long time horizons, the number of pedestrian interactions is high, leading to the degradation of traditional pedestrian trajectory estimation techniques.

Cited by 6SourceScholar
2022

Multi-Modal Non-Isotropic Light Source Modelling for Reflectance Estimation in Hyperspectral Imaging

RA-L 2022

Estimating reflectance is key when working with hyperspectral cameras. The modelling of light sources can aid reflectance estimation, however, it is commonly overlooked. The key contribution of this letter is a physics-based, data-driven model formed by a Gaussian Process (GP) with a unique mean fun

Cited by 0SourceScholar
2021

Probabilistic Dynamic Crowd Prediction for Social Navigation

ICRA 2021poster

In this paper, we present a novel approach that predicts spatially and temporally crowd behaviour for robotic social navigation. Integrating mobile robots into human society involves the fundamental problem of navigation in crowds. A robot should attempt to navigate in a way that is minimally invasi…

Cited by 14SourceScholar
2018

Socially Constrained Tracking in Crowded Environments Using Shoulder Pose Estimates

ICRA 2018poster

Detecting and tracking people is a key requirement in the development of robotic technologies intended to operate in human environments. In crowded environments such as train stations this task is particularly challenging due the high numbers of targets and frequent occlusions. In this paper we pres…

Cited by 3SourceScholar
2016

Exploring in 3D with a climbing robot: Selecting the next best base position on arbitrarily-oriented surfaces

IROS 2016poster

This paper presents an approach for selecting the next best base position for a climbing robot so as to observe the highest information gain about the environment. The robot is capable of adhering to and moving along and transitioning to surfaces with arbitrary orientations. This approach samples kn…

Cited by 8SourceScholar