Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Bogdan Spanjevic

dblp:314/9933 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

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
Health and well-being technologies · 50% Human-robot interaction · 50%
Artificial intelligence
1 paper
Face, body and person analysis · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
affective interaction
0.612022
Sensitive Pictures: Emotional Interpretation in the Museum · CHI 2022
Computer vision › Face, body and person analysis › facial expression analysis
facial expression recognition
0.212022
Sensitive Pictures: Emotional Interpretation in the Museum · CHI 2022

Methods — techniques the papers use, named apart from their topics

computer vision · 1.1
YearPublicationVenuePosition
2022 Sensitive Pictures: Emotional Interpretation in the Museum
abstract
Museums are interested in designing emotional visitor experiences to complement traditional interpretations. HCI is interested in the relationship between Affective Computing and Affective Interaction. We describe Sensitive Pictures, an emotional visitor experience co-created with the Munch art museum. Visitors choose emotions, locate associated paintings in the museum, experience an emotional story while viewing them, and self-report their response. A subsequent interview with a portrayal of the artist employs computer vision to estimate emotional responses from facial expressions. Visitors are given a souvenir postcard visualizing their emotional data. A study of 132 members of the public (39 interviewed) illuminates key themes: designing emotional provocations; capturing emotional responses; engaging visitors with their data; a tendency for them to align their views with the system's interpretation; and integrating these elements into emotional trajectories. We consider how Affective Computing can hold up a mirror to our emotions during Affective Interaction
Steve Benford, Anders Sundnes Løvlie, Karin Ryding, Paulina Rajkowska, Edgar Bodiaj, Dimitrios Paris Darzentas, Harriet R. Cameron, Jocelyn Spence, Joy Egede, Bogdan Spanjevic
CHI10