Demo Data from SIGIR 2026 / reviewers in the wild / expert
Amanda Chicoli
dblp:117/2144
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-2857-4869ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
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.
| Artificial intelligence
1 paper |
Video understanding and tracking · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking
object tracking |
0.1 | 1 | 2012 | Putting the fish in the fish tank: Immersive VR for animal behavior experiments · ICRA 2012 |
Computer vision › Video understanding and tracking › object tracking › 3d object tracking
real-time 3d tracking |
0.1 | 1 | 2012 | Putting the fish in the fish tank: Immersive VR for animal behavior experiments · ICRA 2012 |
Immersive interaction
virtual reality |
0.1 | 1 | 2012 | Putting the fish in the fish tank: Immersive VR for animal behavior experiments · ICRA 2012 |
Methods — techniques the papers use, named apart from their topics
virtual reality · 0.4looming stimulus · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | Putting the fish in the fish tank: Immersive VR for animal behavior experimentsabstractWe describe a virtual-reality framework for investigating startle-response behavior in fish. Using real-time three-dimensional tracking, we generate looming stimuli at a specific location on a computer screen, such that the shape and size of the looming stimuli change according to the fish's perspective and location in the tank. We demonstrate the effectiveness of the setup through experiments on Giant danio and compute the success rate in eliciting a response. We also estimate visual startle sensitivity by presenting the stimulus from different directions around the fish head. The aim of this work is to provide the basis for quantifying escape behavior in fish schools. Sachit Butail, Amanda Chicoli, Derek A. Paley |
ICRA | 2 |