Demo Data from SIGIR 2026 / reviewers in the wild / expert
Aravind Elanjimattathil Vijayan
dblp:226/6428
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0002-0626-5021ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
motion retargeting |
0.3 | 1 | 2018 | Using Constrained Optimization for Real-Time Synchronization of Verbal and Nonverbal Robot Behavior · ICRA 2018 |
Human-robot interaction › nonverbal communication
nonverbal robot behavior |
0.3 | 1 | 2018 | Using Constrained Optimization for Real-Time Synchronization of Verbal and Nonverbal Robot Behavior · ICRA 2018 |
Methods — techniques the papers use, named apart from their topics
quadratic programming · 0.3constrained optimization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Using Constrained Optimization for Real-Time Synchronization of Verbal and Nonverbal Robot BehaviorabstractMost of the motion re-targeting techniques are grounded on virtual character animation research, which means that they typically assume that the target embodiment has unconstrained joint angular velocities. However, because robots often do have such constraints, traditional re-targeting approaches can originate irregular delays in the robot motion. With the goal of ensuring synchronization between verbal and nonverbal behavior, this paper proposes an optimization framework for processing re-targeted motion sequences that addresses constraints such as joint angle and angular velocities. The proposed framework was evaluated on a humanoid robot using both objective and subjective metrics. While the analysis of the joint motion trajectories provides evidence that our framework successfully performs the desired modifications to ensure verbal and nonverbal behavior synchronization, results from a perceptual study showed that participants found the robot motion generated by our method more natural, elegant and lifelike than a control condition. Aravind Elanjimattathil Vijayan, Simon Alexanderson, Jonas Beskow, Iolanda Leite |
ICRA | 1 |