EMBER: Exact Mesh Booleans via Efficient & Robust Local Arrangements

Philip Trettner, Julius Nehring-Wirxel, Leif Kobbelt

Boolean operators are an essential tool in a wide range of geometry processing and CAD/CAM tasks. We present a novel method, EMBER, to compute Boolean operations on polygon meshes which is exact, reliable, and highly performant at the same time. Exactness is guaranteed by using a plane-based representation for the input meshes along with recently introduced homogeneous integer coordinates. Reliability and robustness emerge from a formulation of the algorithm via generalized winding numbers and mesh arrangements. High performance is achieved by avoiding the (pre-)construction of a global acceleration structure. Instead, our algorithm performs an adaptive recursive subdivision of the scene’s bounding box while generating and tracking all required data on the fly. By leveraging a number of early-out termination criteria, we can avoid the generation and inspection of regions that do not contribute to the output. With a careful implementation and a work-stealing multi-threading architecture, we are able to compute Boolean operations between meshes with millions of triangles at interactive rates. We run an extensive evaluation on the Thingi10K dataset to demonstrate that our method outperforms state-of-the-art algorithms, even inexact ones like QuickCSG, by orders of magnitude.

Contact: trettner@shapedcode.com

HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images

Ali Athar, Jonathon Luiten, Alexander Hermans, Deva Ramanan, Bastian Leibe
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral)

Existing state-of-the-art methods for Video Object Segmentation (VOS) learn low-level pixel-to-pixel correspondences between frames to propagate object masks across video. This requires a large amount of densely annotated video data, which is costly to annotate, and largely redundant since frames within a video are highly correlated. In light of this, we propose HODOR: a novel method that tackles VOS by effectively leveraging annotated static images for understanding object appearance and scene context. We encode object instances and scene information from an image frame into robust high-level descriptors which can then be used to re-segment those objects in different frames. As a result, HODOR achieves state-of-the-art performance on the DAVIS and YouTube-VOS benchmarks compared to existing methods trained without video annotations. Without any architectural modification, HODOR can also learn from video context around single annotated video frames by utilizing cyclic consistency, whereas other methods rely on dense, temporally consistent annotations.

» Show BibTeX

title = {{HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images}},
author = {Athar, Ali and Luiten, Jonathon and Hermans, Alexander and Ramanan, Deva and Leibe, Bastian},
journal = {{IEEE Conference on Computer Vision and Pattern Recognition (CVPR'22)}},
year = {2022}

Opening up Open World Tracking

Yang Liu*, Idil Esen Zulfikar*, Jonathon Luiten*, Achal Dave*, Deva Ramanan, Bastian Leibe, Aljoša Ošep, Laura Leal-Taixé
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022 (Oral)

Tracking and detecting any object, including ones never-seen-before during model training, is a crucial but elusive capability of autonomous systems. An autonomous agent that is blind to never-seen-before objects poses a safety hazard when operating in the real world and yet this is how almost all current systems work. One of the main obstacles towards advancing tracking any object is that this task is notoriously difficult to evaluate. A benchmark that would allow us to perform an apples-to-apples comparison of existing efforts is a crucial first step towards advancing this important research field. This paper addresses this evaluation deficit and lays out the landscape and evaluation methodology for detecting and tracking both known and unknown objects in the open-world setting. We propose a new benchmark, TAO-OW: Tracking Any Object in an Open World}, analyze existing efforts in multi-object tracking, and construct a baseline for this task while highlighting future challenges. We hope to open a new front in multi-object tracking research that will hopefully bring us a step closer to intelligent systems that can operate safely in the real world.

» Show BibTeX

title={Opening up Open-World Tracking},
author={Liu, Yang and Zulfikar, Idil Esen and Luiten, Jonathon and Dave, Achal and Ramanan, Deva and Leibe, Bastian and O{\v{s}}ep, Aljo{\v{s}}a and Leal-Taix{\'e}, Laura},
journal={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},

TinyAD: Automatic Differentiation in Geometry Processing Made Simple

Patrick Schmidt, Janis Born, David Bommes, Marcel Campen, Leif Kobbelt
Eurographics Symposium on Geometry Processing 2022

Non-linear optimization is essential to many areas of geometry processing research. However, when experimenting with different problem formulations or when prototyping new algorithms, a major practical obstacle is the need to figure out derivatives of objective functions, especially when second-order derivatives are required. Deriving and manually implementing gradients and Hessians is both time-consuming and error-prone. Automatic differentiation techniques address this problem, but can introduce a diverse set of obstacles themselves, e.g. limiting the set of supported language features, imposing restrictions on a program's control flow, incurring a significant run time overhead, or making it hard to exploit sparsity patterns common in geometry processing. We show that for many geometric problems, in particular on meshes, the simplest form of forward-mode automatic differentiation is not only the most flexible, but also actually the most efficient choice. We introduce TinyAD: a lightweight C++ library that automatically computes gradients and Hessians, in particular of sparse problems, by differentiating small (tiny) sub-problems. Its simplicity enables easy integration; no restrictions on, e.g., looping and branching are imposed. TinyAD provides the basic ingredients to quickly implement first and second order Newton-style solvers, allowing for flexible adjustment of both problem formulations and solver details. By showcasing compact implementations of methods from parametrization, deformation, and direction field design, we demonstrate how TinyAD lowers the barrier to exploring non-linear optimization techniques. This enables not only fast prototyping of new research ideas, but also improves replicability of existing algorithms in geometry processing. TinyAD is available to the community as an open source library.

» Show BibTeX

title={{TinyAD}: Automatic Differentiation in Geometry Processing Made Simple},
author={Schmidt, Patrick and Born, Janis and Bommes, David and Campen, Marcel and Kobbelt, Leif},
journal={Computer Graphics Forum},

A Survey on SPH Methods in Computer Graphics

Dan Koschier, Jan Bender, Barbara Solenthaler, Matthias Teschner
Computer Graphics Forum

Throughout the past decades, the graphics community has spent major resources on the research and development of physics simulators on the mission to computer-generate behaviors achieving outstanding visual effects or to make the virtual world indistinguishable from reality. The variety and impact of recent research based on Smoothed Particle Hydrodynamics (SPH) demonstrates the concept's importance as one of the most versatile tools for the simulation of fluids and solids. With this survey, we offer an overview of the developments and still-active research on physics simulation methodologies based on SPH that has not been addressed in previous SPH surveys. Following an introduction about typical SPH discretization techniques, we provide an overview over the most used incompressibility solvers and present novel insights regarding their relation and conditional equivalence. The survey further covers recent advances in implicit and particle-based boundary handling and sampling techniques. While SPH is best known in the context of fluid simulation we discuss modern concepts to augment the range of simulatable physical characteristics including turbulence, highly viscous matter, deformable solids, as well as rigid body contact handling. Besides the purely numerical approaches, simulation techniques aided by machine learning are on the rise. Thus, the survey discusses recent data-driven approaches and the impact of differentiable solvers on artist control. Finally, we provide context for discussion by outlining existing problems and opportunities to open up new research directions.

» Show BibTeX

@article {KBST2022,
journal = {Computer Graphics Forum},
title = {{A Survey on SPH Methods in Computer Graphics}},
author = {Koschier, Dan and Bender, Jan and Solenthaler, Barbara and Teschner, Matthias},
year = {2022},
volume ={41},
number = {2},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14508}

Performance Assessment of Diffusive Load Balancing for Distributed Particle Advection

Ali Can Demiralp, Dirk Norbert Helmrich, Joachim Protze, Torsten Wolfgang Kuhlen, Tim Gerrits
30. International Conference in Central Europe on Computer Graphics, Visualization, and Computer Vision 2022 (WSCG2022)

Particle advection is the approach for the extraction of integral curves from vector fields. Efficient parallelization of particle advection is a challenging task due to the problem of load imbalance, in which processes are assigned unequal workloads, causing some of them to idle as the others are performing computing. Various approaches to load balancing exist, yet they all involve trade-offs such as increased inter-process communication, or the need for central control structures. In this work, we present two local load balancing methods for particle advection based on the family of diffusive load balancing. Each process has access to the blocks of its neighboring processes, which enables dynamic sharing of the particles based on a metric defined by the workload of the neighborhood. The approaches are assessed in terms of strong and weak scaling as well as load imbalance. We show that the methods reduce the total run-time of advection and are promising with regard to scaling as they operate locally on isolated process neighborhoods.

Pseudodynamic analysis of heart tube formation in the mouse reveals strong regional variability and early left–right asymmetry

Isaac Esteban, Patrick Schmidt, Audrey Desgrange, Morena Raiola, Susana Temiño, Sigolène Meilhac, Leif Kobbelt, Miguel Torres
Nature Cardiovascular Research

Understanding organ morphogenesis requires a precise geometrical description of the tissues involved in the process. The high morphological variability in mammalian embryos hinders the quantitative analysis of organogenesis. In particular, the study of early heart development in mammals remains a challenging problem due to imaging limitations and complexity. Here, we provide a complete morphological description of mammalian heart tube formation based on detailed imaging of a temporally dense collection of mouse embryonic hearts. We develop strategies for morphometric staging and quantification of local morphological variations between specimens. We identify hot spots of regionalized variability and identify Nodal-controlled left–right asymmetry of the inflow tracts as the earliest signs of organ left–right asymmetry in the mammalian embryo. Finally, we generate a three-dimensional+t digital model that allows co-representation of data from different sources and provides a framework for the computer modeling of heart tube formation.

» Show BibTeX

author = {Esteban, Isaac and Schmidt, Patrick and Desgrange, Audrey and Raiola, Morena and Temi{\~n}o, Susana and Meilhac, Sigol\`{e}ne M. and Kobbelt, Leif and Torres, Miguel},
title = {Pseudo-dynamic analysis of heart tube formation in the mouse reveals strong regional variability and early left-right asymmetry},
year = {2022},
journal = {Nature Cardiovascular Research},
volume = 1,
number = 5

Quantitative Mapping of Keratin Networks in 3D

Reinhard Windoffer, Nicole Schwarz, Sungjun Yoon, Teodora Piskova, Michael Scholkemper, Johannes Stegmaier, Andrea Bönsch, Jacopo Di Russo, Rudolf E. Leube

Mechanobiology requires precise quantitative information on processes taking place in specific 3D microenvironments. Connecting the abundance of microscopical, molecular, biochemical, and cell mechanical data with defined topologies has turned out to be extremely difficult. Establishing such structural and functional 3D maps needed for biophysical modeling is a particular challenge for the cytoskeleton, which consists of long and interwoven filamentous polymers coordinating subcellular processes and interactions of cells with their environment. To date, useful tools are available for the segmentation and modeling of actin filaments and microtubules but comprehensive tools for the mapping of intermediate filament organization are still lacking. In this work, we describe a workflow to model and examine the complete 3D arrangement of the keratin intermediate filament cytoskeleton in canine, murine, and human epithelial cells both, in vitro and in vivo. Numerical models are derived from confocal Airyscan high-resolution 3D imaging of fluorescence-tagged keratin filaments. They are interrogated and annotated at different length scales using different modes of visualization including immersive virtual reality. In this way, information is provided on network organization at the subcellular level including mesh arrangement, density, and isotropic configuration as well as details on filament morphology such as bundling, curvature, and orientation. We show that the comparison of these parameters helps to identify, in quantitative terms, similarities and differences of keratin network organization in epithelial cell types defining subcellular domains, notably basal, apical, lateral, and perinuclear systems. The described approach and the presented data are pivotal for generating mechanobiological models that can be experimentally tested.

» Show BibTeX

@article {Windoffer2022,
article_type = {journal},
title = {{Quantitative Mapping of Keratin Networks in 3D}},
author = {Windoffer, Reinhard and Schwarz, Nicole and Yoon, Sungjun and Piskova, Teodora and Scholkemper, Michael and Stegmaier, Johannes and Bönsch, Andrea and Di Russo, Jacopo and Leube, Rudolf},
editor = {Coulombe, Pierre},
volume = 11,
year = 2022,
month = {feb},
pub_date = {2022-02-18},
pages = {e75894},
citation = {eLife 2022;11:e75894},
doi = {10.7554/eLife.75894},
url = {https://doi.org/10.7554/eLife.75894},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},

Quantitative Evaluation of SPH in TIG Spot Welding

Stefan Rhys Jeske, Marek Simon, Oleksii Semenov, Jan Kruska, Oleg Mokrov, Rahul Sharma, Uwe Reisgen, Jan Bender
Computational Particle Mechanics

While the application of the Smoothed Particle Hydrodynamics (SPH) method for the modeling of welding processes has become increasingly popular in recent years, little is yet known about the quantitative predictive capability of this method. We propose a novel SPH model for the simulation of the tungsten inert gas (TIG) spot welding process and conduct a thorough comparison between our SPH implementation and two Finite Element Method (FEM) based models. In order to be able to quantitatively compare the results of our SPH simulation method with grid based methods we additionally propose an improved particle to grid interpolation method based on linear least-squares with an optional hole-filling pass which accounts for missing particles. We show that SPH is able to yield excellent results, especially given the observed deviations between the investigated FEM methods and as such, we validate the accuracy of the method for an industrially relevant engineering application.

» Show BibTeX

author = {Stefan Rhys Jeske and Marek Sebastian Simon and Oleksii Semenov and Jan Kruska and Oleg Mokrov and Rahul Sharma and Uwe Reisgen and Jan Bender},
journal = {Computational Particle Mechanics},
title = {Quantitative evaluation of {SPH} in {TIG} spot welding},
year = {2022},
month = {apr},
doi = {10.1007/s40571-022-00465-x},
publisher = {Springer Science and Business Media {LLC}},

Application and Benchmark of SPH for Modeling the Impact in Thermal Spraying

Stefan Rhys Jeske, Jan Bender, Kirsten Bobzin, Hendrik Heinemann, Kevin Jasutyn, Marek Simon, Oleg Mokrov, Rahul Sharma, Uwe Reisgen
Computational Particle Mechanics

The properties of a thermally sprayed coating, such as its durability or thermal conductivity depend on its microstructure, which is in turn directly related to the particle impact process. To simulate this process we present a 3D Smoothed Particle Hydrodynamics (SPH) model, which represents the molten droplet as an incompressible fluid, while a semi-implicit Enthalpy-Porosity method is applied for modeling the phase change during solidification. In addition, we present an implicit correction for SPH simulations, based on well known approaches, from which we can observe improved performance and simulation stability. We apply our SPH method to the impact and solidification of Al2O3 droplets onto a substrate and perform a comprehensive quantitative comparison of our method with the commercial software Ansys Fluent using the Volume of Fluid (VOF) approach, while taking identical physical effects into consideration. The results are evaluated in depth and we discuss the applicability of either method for the simulation of thermal spray deposition. We also evaluate the droplet spread factor given varying initial droplet diameters and compare these results with an analytic expression from previous literature. We show that SPH is an excellent method for solving this free surface problem accurately and efficiently.

» Show BibTeX

author = {Stefan Rhys Jeske and Jan Bender and Kirsten Bobzin and Hendrik Heinemann and Kevin Jasutyn and Marek Simon and Oleg Mokrov and Rahul Sharma and Uwe Reisgen},
journal = {Computational Particle Mechanics},
title = {Application and benchmark of {SPH} for modeling the impact in thermal spraying},
year = {2022},
month = {jan},
doi = {10.1007/s40571-022-00459-9},
publisher = {Springer Science and Business Media {LLC}},

Augmented Reality-Based Surgery on the Human Cadaver Using a New Generation of Optical Head-Mounted Displays: Development and Feasibility Study

Behrus Puladi, Mark Ooms, Martin Bellgardt, Mark Cesov, Myriam Lipprandt, Stefan Raith, Florian Peters, Stephan Christian Möhlhenrich, Andreas Prescher, Frank Hölzle, Torsten Wolfgang Kuhlen, Ali Modabber
JMIR Serious Games 2022

Background: Although nearly one-third of the world’s disease burden requires surgical care, only a small proportion of digital health applications are directly used in the surgical field. In the coming decades, the application of augmented reality (AR) with a new generation of optical-see-through head-mounted displays (OST-HMDs) like the HoloLens (Microsoft Corp) has the potential to bring digital health into the surgical field. However, for the application to be performed on a living person, proof of performance must first be provided due to regulatory requirements. In this regard, cadaver studies could provide initial evidence.

Objective: The goal of the research was to develop an open-source system for AR-based surgery on human cadavers using freely available technologies.

Methods: We tested our system using an easy-to-understand scenario in which fractured zygomatic arches of the face had to be repositioned with visual and auditory feedback to the investigators using a HoloLens. Results were verified with postoperative imaging and assessed in a blinded fashion by 2 investigators. The developed system and scenario were qualitatively evaluated by consensus interview and individual questionnaires.

Results: The development and implementation of our system was feasible and could be realized in the course of a cadaver study. The AR system was found helpful by the investigators for spatial perception in addition to the combination of visual as well as auditory feedback. The surgical end point could be determined metrically as well as by assessment.

Conclusions: The development and application of an AR-based surgical system using freely available technologies to perform OST-HMD–guided surgical procedures in cadavers is feasible. Cadaver studies are suitable for OST-HMD–guided interventions to measure a surgical end point and provide an initial data foundation for future clinical trials. The availability of free systems for researchers could be helpful for a possible translation process from digital health to AR-based surgery using OST-HMDs in the operating theater via cadaver studies.

» Show BibTeX

title={Augmented Reality-Based Surgery on the Human Cadaver Using a New Generation of Optical Head-Mounted Displays: Development and Feasibility Study},
author={Puladi, Behrus and Ooms, Mark and Bellgardt, Martin and Cesov, Mark and Lipprandt, Myriam and Raith, Stefan and Peters, Florian and M{\"o}hlhenrich, Stephan Christian and Prescher, Andreas and H{\"o}lzle, Frank and others},
journal={JMIR Serious Games},
publisher={JMIR Publications Inc., Toronto, Canada}

The aixCAVE at RWTH Aachen University

Torsten Wolfgang Kuhlen, Geert Mathys
In Chapter 09 "VR/AR Use Cases" of "Virtual and Augmented Reality - Foundations and Methods of Extended Realities"

At a large technical university like RWTH Aachen, there is enormous potential to use VR as a tool in research. In contrast to applications from the entertainment sector, many scientific application scenarios - for example, a 3D analysis of result data from simulated flows - not only depend on a high degree of immersion, but also on a high resolution and excellent image quality of the display. In addition, the visual analysis of scientific data is often carried out and discussed in smaller teams. For these reasons, but also for simple ergonomic aspects (comfort, cybersickness), many technical and scientific VR applications cannot just be implemented on the basis of head-mounted displays. To this day, in VR Labs of universities and research institutions, it is therefore desirable to install immersive large-screen rear projection systems (CAVEs) in order to adequately support the scientists. Due to the high investment costs, such systems are used at larger universities such as Aachen, Cologne, Munich, or Stuttgart, often operated by the computing centers as a central infrastructure accessible to all scientists at the university.

4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation

Lars Kreuzberg, Idil Esen Zulfikar, Sabarinath Mahadevan, Francis Engelmann, Bastian Leibe
IEEE European Conference on Computer Vision (ECCV) 2022, AVVision Workshop

In this work, we present a new paradigm, called 4D-StOP, to tackle the task of 4D Panoptic LiDAR Segmentation. 4D-StOP first generates spatio-temporal proposals using voting-based center predictions, where each point in the 4D volume votes for a corresponding center. These tracklet proposals are further aggregated using learned geometric features. The tracklet aggregation method effectively generates a video-level 4D scene representation over the entire space-time volume. This is in contrast to existing end-to-end trainable state-of-the-art approaches which use spatio-temporal embeddings that are represented by Gaussian probability distributions. Our voting-based tracklet generation method followed by geometric feature-based aggregation generates significantly improved panoptic LiDAR segmentation quality when compared to modeling the entire 4D volume using Gaussian probability distributions. 4D-StOP achieves a new state-of-the-art when applied to the SemanticKITTI test dataset with a score of 63.9 LSTQ, which is a large (+7%) improvement compared to current best-performing end-to-end trainable methods. The code and pre-trained models are available at:https://github.com/LarsKreuzberg/4D-StOP

Global Hierarchical Attention for 3D Point Cloud Analysis

Dan Jia, Alexander Hermans, Bastian Leibe
German Conference on Pattern Recognition (GCPR) 2022

We propose a new attention mechanism, called Global Hierarchical Attention (GHA), for 3D point cloud analysis. GHA approximates the regular global dot-product attention via a series of coarsening and interpolation operations over multiple hierarchy levels. The advantage of GHA is two-fold. First, it has linear complexity with respect to the number of points, enabling the processing of large point clouds. Second, GHA inherently possesses the inductive bias to focus on spatially close points, while retaining the global connectivity among all points. Combined with a feedforward network, GHA can be inserted into many existing network architectures. We experiment with multiple baseline networks and show that adding GHA consistently improves performance across different tasks and datasets. For the task of semantic segmentation, GHA gives a +1.7% mIoU increase to the MinkowskiEngine baseline on ScanNet. For the 3D object detection task, GHA improves the CenterPoint baseline by +0.5% mAP on the nuScenes dataset, and the 3DETR baseline by +2.1% mAP25 and +1.5% mAP50 on ScanNet.

Pedestrian-Robot Interactions on Autonomous Crowd Navigation: Reactive Control Methods and Evaluation Metrics

Diego Paez-Granados, Yujie He, David Gonon, Dan Jia, Bastian Leibe, Kenji Suzuki, Aude Billard
International Conference on Intelligent Robots and Systems (IROS) 2022

Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations. In this work, we present a crowd navigation control framework that delivers continuous obstacle avoidance and post-contact control evaluated on an autonomous personal mobility vehicle. We propose evaluation metrics for accounting efficiency, controller response and crowd interactions in natural crowds. We report the results of over 110 trials in different crowd types: sparse, flows, and mixed traffic, with low- (< 0.15 ppsm), mid- (< 0.65 ppsm), and high- (< 1 ppsm) pedestrian densities. We present comparative results between two low-level obstacle avoidance methods and a baseline of shared control. Results show a 10% drop in relative time to goal on the highest density tests, and no other efficiency metric decrease. Moreover, autonomous navigation showed to be comparable to shared-control navigation with a lower relative jerk and significantly higher fluency in commands indicating high compatibility with the crowd. We conclude that the reactive controller fulfills a necessary task of fast and continuous adaptation to crowd navigation, and it should be coupled with high-level planners for environmental and situational awareness.

Differentiable Soft-Masked Attention

Ali Athar, Jonathon Luiten, Alexander Hermans, Deva Ramanan, Bastian Leibe
Transformers for Vision Workshop at CVPR 2022

Transformers have become prevalent in computer vision due to their performance and flexibility in modelling complex operations. Of particular significance is the ‘cross-attention’ operation, which allows a vector representation (e.g. of an object in an image) to be learned by ‘attending’ to an arbitrarily sized set of input features. Recently, ‘Masked Attention’ was proposed in which a given object representation only attends to those image pixel features for which the segmentation mask of that object is active. This specialization of attention proved beneficial for various image and video segmentation tasks. In this paper, we propose another specialization of attention which enables attending over ‘soft-masks’ (those with continuous mask probabilities instead of binary values), and is also differentiable through these mask probabilities, thus allowing the mask used for attention to be learned within the network without requiring direct loss supervision. This can be useful for several applications. Specifically, we employ our ‘Differentiable Soft-Masked Attention’ for the task of Weakly Supervised Video Object Segmentation (VOS), where we develop a transformer-based network for VOS which only requires a single annotated image frame for training, but can also benefit from cycle consistency training on a video with just one annotated frame. Although there is no loss for masks in unlabeled frames, the network is still able to segment objects in those frames due to our novel attention formulation.

Late-Breaking Report: Natural Turn-Taking with Embodied Conversational Agents

Jonathan Ehret, Andrea Bönsch, Torsten Wolfgang Kuhlen
IEEE Virtual Humans and Crowds for Immersive Environments (VHCIE), 2022

Adding embodied conversational agents (ECAs) to immersive virtual environments (IVEs) becomes relevant in various application scenarios, for example, conversational systems. For successful interactions with these ECAs, they have to behave naturally, i.e. in the way a user would expect a real human to behave. Teaming up with acousticians and psychologists, we strive to explore turn-taking in VR-based interactions between either two ECAs or an ECA and a human user.

Late-Breaking Report: An Embodied Conversational Agent Supporting Scene Exploration by Switching between Guiding and Accompanying

Andrea Bönsch, Daniel Rupp, Jonathan Ehret, Torsten Wolfgang Kuhlen
IEEE Virtual Humans and Crowds for Immersive Environments (VHCIE), 2022

In this late-breaking report, we first motivate the requirement of an embodied conversational agent (ECA) who combines characteristics of a virtual tour guide and a knowledgeable companion in order to allow users an interactive and adaptable, however, structured exploration of an unknown immersive, architectural environment. Second, we roughly outline our proposed ECA’s behavioral design followed by a teaser on the planned user study.

2D vs. 3D LiDAR-based Person Detection on Mobile Robots

Dan Jia, Alexander Hermans, Bastian Leibe
International Conference on Intelligent Robots and Systems (IROS) 2022

Person detection is a crucial task for mobile robots navigating in human-populated environments. LiDAR sensors are promising for this task, thanks to their accurate depth measurements and large field of view. Two types of LiDAR sensors exist: the 2D LiDAR sensors, which scan a single plane, and the 3D LiDAR sensors, which scan multiple planes, thus forming a volume. How do they compare for the task of person detection? To answer this, we conduct a series of experiments, using the public, large-scale JackRabbot dataset and the state-of-the-art 2D and 3D LiDAR-based person detectors (DR-SPAAM and CenterPoint respectively). Our experiments include multiple aspects, ranging from the basic performance and speed comparison, to more detailed analysis on localization accuracy and robustness against distance and scene clutter. The insights from these experiments highlight the strengths and weaknesses of 2D and 3D LiDAR sensors as sources for person detection, and are especially valuable for designing mobile robots that will operate in close proximity to surrounding humans (e.g. service or social robot).

Previous Year (2021)
Disclaimer Home Visual Computing institute RWTH Aachen University