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Amanda Chicoli

dblp:117/2144 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Computer vision › Video understanding and tracking
object tracking
0.112012
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
0.112012
Putting the fish in the fish tank: Immersive VR for animal behavior experiments · ICRA 2012
Immersive interaction
virtual reality
0.112012
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
YearPublicationVenuePosition
2012 Putting the fish in the fish tank: Immersive VR for animal behavior experiments
abstract
We 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
ICRA2