---
_id: '63611'
abstract:
- lang: eng
text: When humans interact with artificial intelligence (AI), one desideratum is
appropriate trust. Typically, appropriate trust encompasses that humans trust
AI except for instances in which they either explicitly notice AI errors or are
suspicious that errors could be present. So far, appropriate trust or related
notions have mainly been investigated by assessing trust and reliance. In this
contribution, we argue that these assessments are insufficient to measure the
complex aim of appropriate trust and the related notion of healthy distrust. We
introduce and test the perspective of covert visual attention as an additional
indicator for appropriate trust and draw conceptual connections to the notion
of healthy distrust. To test the validity of our conceptualization, we formalize
visual attention using the Theory of Visual Attention and measure its properties
that are potentially relevant to appropriate trust and healthy distrust in an
image classification task. Based on temporal-order judgment performance, we estimate
participants' attentional capacity and attentional weight toward correct and incorrect
mock-up AI classifications. We observe that misclassifications reduce attentional
capacity compared to correct classifications. However, our results do not indicate
that this reduction is beneficial for a subsequent judgment of the classifications.
The attentional weighting is not affected by the classifications' correctness
but by the difficulty of categorizing the stimuli themselves. We discuss these
results, their implications, and the limited potential for using visual attention
as an indicator of appropriate trust and healthy distrust.
article_number: '1694367'
article_type: original
author:
- first_name: Tobias Martin
full_name: Peters, Tobias Martin
id: '92810'
last_name: Peters
orcid: 0009-0008-5193-6243
- first_name: Kai
full_name: Biermeier, Kai
id: '55908'
last_name: Biermeier
orcid: 0000-0002-2879-2359
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: 'Peters TM, Biermeier K, Scharlau I. Assessing healthy distrust in human-AI
interaction: interpreting changes in visual attention. Frontiers in Psychology.
2026;16. doi:10.3389/fpsyg.2025.1694367'
apa: 'Peters, T. M., Biermeier, K., & Scharlau, I. (2026). Assessing healthy
distrust in human-AI interaction: interpreting changes in visual attention. Frontiers
in Psychology, 16, Article 1694367. https://doi.org/10.3389/fpsyg.2025.1694367'
bibtex: '@article{Peters_Biermeier_Scharlau_2026, title={Assessing healthy distrust
in human-AI interaction: interpreting changes in visual attention}, volume={16},
DOI={10.3389/fpsyg.2025.1694367},
number={1694367}, journal={Frontiers in Psychology}, publisher={Frontiers Media
SA}, author={Peters, Tobias Martin and Biermeier, Kai and Scharlau, Ingrid}, year={2026}
}'
chicago: 'Peters, Tobias Martin, Kai Biermeier, and Ingrid Scharlau. “Assessing
Healthy Distrust in Human-AI Interaction: Interpreting Changes in Visual Attention.”
Frontiers in Psychology 16 (2026). https://doi.org/10.3389/fpsyg.2025.1694367.'
ieee: 'T. M. Peters, K. Biermeier, and I. Scharlau, “Assessing healthy distrust
in human-AI interaction: interpreting changes in visual attention,” Frontiers
in Psychology, vol. 16, Art. no. 1694367, 2026, doi: 10.3389/fpsyg.2025.1694367.'
mla: 'Peters, Tobias Martin, et al. “Assessing Healthy Distrust in Human-AI Interaction:
Interpreting Changes in Visual Attention.” Frontiers in Psychology, vol.
16, 1694367, Frontiers Media SA, 2026, doi:10.3389/fpsyg.2025.1694367.'
short: T.M. Peters, K. Biermeier, I. Scharlau, Frontiers in Psychology 16 (2026).
date_created: 2026-01-14T14:21:59Z
date_updated: 2026-01-14T14:29:03Z
department:
- _id: '424'
- _id: '660'
doi: 10.3389/fpsyg.2025.1694367
intvolume: ' 16'
keyword:
- appropriate trust
- healthy distrust
- visual attention
- Theory of Visual Attention
- human-AI interaction
- Bayesian cognitive model
- image classification
language:
- iso: eng
project:
- _id: '124'
name: 'TRR 318 ; TP C01: Gesundes Misstrauen in Erklärungen'
publication: Frontiers in Psychology
publication_identifier:
issn:
- 1664-1078
publication_status: published
publisher: Frontiers Media SA
status: public
title: 'Assessing healthy distrust in human-AI interaction: interpreting changes in
visual attention'
type: journal_article
user_id: '92810'
volume: 16
year: '2026'
...
---
_id: '59755'
abstract:
- lang: eng
text: "Due to the application of Artificial Intelligence (AI) in high-risk domains
like law or medicine,\r\ntrustworthy AI and trust in AI are of increasing scientific
and public relevance. A typical conception,\r\nfor example in the context of medical
diagnosis, is that a knowledgeable user receives AIgenerated\r\nclassification
as advice. Research to improve such interactions often aims to foster the\r\nuser’s
trust, which in turn should improve the combined human-AI performance. Given that
AI\r\nmodels can err, we argue that the possibility to critically review, thus
to distrust, an AI decision is\r\nan equally interesting target of research.\r\nWe
created two image classification scenarios in which the participants received
mock-up\r\nAI advice. The quality of the advice decreases for a phase of the experiment.
We studied the\r\ntask performance, trust and distrust of the participants, and
tested whether an instruction to\r\nremain skeptical and review each piece of
advice led to a better performance compared to a\r\nneutral condition. Our results
indicate that this instruction does not improve but rather worsens\r\nthe participants’
performance. Repeated single-item self-report of trust and distrust shows an\r\nincrease
in trust and a decrease in distrust after the drop in the AI’s classification
quality, with no\r\ndifference between the two instructions. Furthermore, via
a Bayesian Signal Detection Theory\r\nanalysis, we provide a procedure to assess
appropriate reliance in detail, by quantifying whether\r\nthe problems of under-
and over-reliance have been mitigated. We discuss implications of our\r\nresults
for the usage of disclaimers before interacting with AI, as prominently used in
current\r\nLLM-based chatbots, and for trust and distrust research."
article_type: original
author:
- first_name: Tobias Martin
full_name: Peters, Tobias Martin
id: '92810'
last_name: Peters
orcid: 0009-0008-5193-6243
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: 'Peters TM, Scharlau I. Interacting with fallible AI: Is distrust helpful when
receiving AI misclassifications? Frontiers in Psychology. 2025;16. doi:10.3389/fpsyg.2025.1574809'
apa: 'Peters, T. M., & Scharlau, I. (2025). Interacting with fallible AI: Is
distrust helpful when receiving AI misclassifications? Frontiers in Psychology,
16. https://doi.org/10.3389/fpsyg.2025.1574809'
bibtex: '@article{Peters_Scharlau_2025, title={Interacting with fallible AI: Is
distrust helpful when receiving AI misclassifications?}, volume={16}, DOI={10.3389/fpsyg.2025.1574809},
journal={Frontiers in Psychology}, author={Peters, Tobias Martin and Scharlau,
Ingrid}, year={2025} }'
chicago: 'Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible
AI: Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in
Psychology 16 (2025). https://doi.org/10.3389/fpsyg.2025.1574809.'
ieee: 'T. M. Peters and I. Scharlau, “Interacting with fallible AI: Is distrust
helpful when receiving AI misclassifications?,” Frontiers in Psychology,
vol. 16, 2025, doi: 10.3389/fpsyg.2025.1574809.'
mla: 'Peters, Tobias Martin, and Ingrid Scharlau. “Interacting with Fallible AI:
Is Distrust Helpful When Receiving AI Misclassifications?” Frontiers in Psychology,
vol. 16, 2025, doi:10.3389/fpsyg.2025.1574809.'
short: T.M. Peters, I. Scharlau, Frontiers in Psychology 16 (2025).
date_created: 2025-05-02T09:22:39Z
date_updated: 2025-05-27T09:10:09Z
department:
- _id: '424'
- _id: '660'
doi: 10.3389/fpsyg.2025.1574809
intvolume: ' 16'
keyword:
- trust in AI
- trust
- distrust
- human-AI interaction
- Signal Detection Theory
- Bayesian parameter estimation
- image classification
language:
- iso: eng
project:
- _id: '124'
name: 'TRR 318 - C1: TRR 318 - Subproject C1 - Gesundes Misstrauen in Erklärungen'
publication: Frontiers in Psychology
publication_status: published
status: public
title: 'Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?'
type: journal_article
user_id: '92810'
volume: 16
year: '2025'
...
---
_id: '55196'
author:
- first_name: Christoph
full_name: Jacke, Christoph
id: '20747'
last_name: Jacke
citation:
ama: 'Jacke C. Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild und
Entwicklungstendenzen im deutschen Schlager. Musiktheorie Zeitschrift für Musikwissenschaft.
2024;39(2):181-185.'
apa: 'Jacke, C. (2024). Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild
und Entwicklungstendenzen im deutschen Schlager. In Musiktheorie. Zeitschrift
für Musikwissenschaft. (Vol. 39, Issue 2, pp. 181–185). Laaber.'
bibtex: '@article{Jacke_2024, place={Lilienthal}, title={Marina Forell (2023): Atemlos
zum Erfolg. Gender, Frauenbild und Entwicklungstendenzen im deutschen Schlager.},
volume={39}, number={2}, journal={Musiktheorie. Zeitschrift für Musikwissenschaft.},
publisher={Laaber}, author={Jacke, Christoph}, year={2024}, pages={181–185} }'
chicago: 'Jacke, Christoph. “Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild
und Entwicklungstendenzen im deutschen Schlager.” Musiktheorie. Zeitschrift
für Musikwissenschaft. Lilienthal: Laaber, 2024.'
ieee: 'C. Jacke, “Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild und
Entwicklungstendenzen im deutschen Schlager.,” Musiktheorie. Zeitschrift für
Musikwissenschaft., vol. 39, no. 2. Laaber, Lilienthal, pp. 181–185, 2024.'
mla: 'Jacke, Christoph. “Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild
und Entwicklungstendenzen im deutschen Schlager.” Musiktheorie. Zeitschrift
für Musikwissenschaft., vol. 39, no. 2, Laaber, 2024, pp. 181–85.'
short: C. Jacke, Musiktheorie. Zeitschrift für Musikwissenschaft. 39 (2024) 181–185.
date_created: 2024-07-12T15:30:18Z
date_updated: 2026-03-05T12:23:56Z
ddc:
- '780'
department:
- _id: '607'
- _id: '817'
file:
- access_level: closed
content_type: application/pdf
creator: jackech
date_created: 2024-07-29T09:27:03Z
date_updated: 2024-07-29T09:27:03Z
file_id: '55413'
file_name: 181-185_Rombach.pdf
file_size: 82983
relation: main_file
success: 1
file_date_updated: 2024-07-29T09:27:03Z
has_accepted_license: '1'
intvolume: ' 39'
issue: '2'
keyword:
- Popmusik
- Gender
- Schlager
- Frauen
- Image
- Deutschland
language:
- iso: ger
page: 181-185
place: Lilienthal
publication: Musiktheorie. Zeitschrift für Musikwissenschaft.
publication_identifier:
issn:
- 0177-4182
publication_status: published
publisher: Laaber
related_material:
link:
- relation: confirmation
url: https://laaber-verlag.de/listview?link=0107001
status: public
title: 'Marina Forell (2023): Atemlos zum Erfolg. Gender, Frauenbild und Entwicklungstendenzen
im deutschen Schlager.'
type: review
user_id: '20747'
volume: 39
year: '2024'
...
---
_id: '22481'
abstract:
- lang: eng
text: During the industrial processing of materials for the manufacture of new products,
surface defects can quickly occur. In order to achieve high quality without a
long time delay, it makes sense to inspect the work pieces so that defective work
pieces can be sorted out right at the beginning of the process. At the same time,
the evaluation unit should come close the perception of the human eye regarding
detection of defects in surfaces. Such defects often manifest themselves by a
deviation of the existing structure. The only restriction should be that only
matt surfaces should be considered here. Therefore in this work, different classification
and image processing algorithms are applied to surface data to identify possible
surface damages. For this purpose, the Gabor filter and the FST (Fused Structure
and Texture) features generated with it, as well as the salience metric are used
on the image processing side. On the classification side, however, deep neural
networks, Convolutional Neural Networks (CNN), and autoencoders are used to make
a decision. A distinction is also made between training using class labels and
without. It turns out later that the salience metric are best performed by CNN.
On the other hand, if there is no labeled training data available, a novelty classification
can easily be achieved by using autoencoders as well as the salience metric and
some filters.
author:
- first_name: Tom
full_name: Sander, Tom
last_name: Sander
- first_name: Sven
full_name: Lange, Sven
id: '38240'
last_name: Lange
- first_name: Ulrich
full_name: Hilleringmann, Ulrich
last_name: Hilleringmann
- first_name: Volker
full_name: Geneis, Volker
last_name: Geneis
- first_name: Christian
full_name: Hedayat, Christian
last_name: Hedayat
- first_name: Harald
full_name: Kuhn, Harald
last_name: Kuhn
- first_name: Franz-Barthold
full_name: Gockel, Franz-Barthold
last_name: Gockel
citation:
ama: 'Sander T, Lange S, Hilleringmann U, et al. Detection of Defects on Irregular
Structured Surfaces by Image Processing Methods for Feature Extraction. In: 22nd
IEEE International Conference on Industrial Technology (ICIT). Valencia, Spain
: IEEE; 2021. doi:10.1109/icit46573.2021.9453646'
apa: 'Sander, T., Lange, S., Hilleringmann, U., Geneis, V., Hedayat, C., Kuhn, H.,
& Gockel, F.-B. (2021). Detection of Defects on Irregular Structured Surfaces
by Image Processing Methods for Feature Extraction. In 22nd IEEE International
Conference on Industrial Technology (ICIT). Valencia, Spain : IEEE. https://doi.org/10.1109/icit46573.2021.9453646'
bibtex: '@inproceedings{Sander_Lange_Hilleringmann_Geneis_Hedayat_Kuhn_Gockel_2021,
place={Valencia, Spain }, title={Detection of Defects on Irregular Structured
Surfaces by Image Processing Methods for Feature Extraction}, DOI={10.1109/icit46573.2021.9453646},
booktitle={22nd IEEE International Conference on Industrial Technology (ICIT)},
publisher={IEEE}, author={Sander, Tom and Lange, Sven and Hilleringmann, Ulrich
and Geneis, Volker and Hedayat, Christian and Kuhn, Harald and Gockel, Franz-Barthold},
year={2021} }'
chicago: 'Sander, Tom, Sven Lange, Ulrich Hilleringmann, Volker Geneis, Christian
Hedayat, Harald Kuhn, and Franz-Barthold Gockel. “Detection of Defects on Irregular
Structured Surfaces by Image Processing Methods for Feature Extraction.” In 22nd
IEEE International Conference on Industrial Technology (ICIT). Valencia, Spain
: IEEE, 2021. https://doi.org/10.1109/icit46573.2021.9453646.'
ieee: T. Sander et al., “Detection of Defects on Irregular Structured Surfaces
by Image Processing Methods for Feature Extraction,” in 22nd IEEE International
Conference on Industrial Technology (ICIT), Valencia, Spain , 2021.
mla: Sander, Tom, et al. “Detection of Defects on Irregular Structured Surfaces
by Image Processing Methods for Feature Extraction.” 22nd IEEE International
Conference on Industrial Technology (ICIT), IEEE, 2021, doi:10.1109/icit46573.2021.9453646.
short: 'T. Sander, S. Lange, U. Hilleringmann, V. Geneis, C. Hedayat, H. Kuhn, F.-B.
Gockel, in: 22nd IEEE International Conference on Industrial Technology (ICIT),
IEEE, Valencia, Spain , 2021.'
conference:
end_date: 2021-03-12
location: 'Valencia, Spain '
name: 22nd IEEE International Conference on Industrial Technology (ICIT)
start_date: 2021-03-10
date_created: 2021-06-20T23:32:11Z
date_updated: 2022-01-06T06:55:33Z
department:
- _id: '59'
- _id: '485'
doi: 10.1109/icit46573.2021.9453646
keyword:
- Image Processing
- Defect Detection
- wooden surfaces
- Machine Learning
- Neural Networks
language:
- iso: eng
main_file_link:
- url: https://ieeexplore.ieee.org/document/9453646
place: 'Valencia, Spain '
publication: 22nd IEEE International Conference on Industrial Technology (ICIT)
publication_identifier:
isbn:
- '9781728157306'
publication_status: published
publisher: IEEE
status: public
title: Detection of Defects on Irregular Structured Surfaces by Image Processing Methods
for Feature Extraction
type: conference
user_id: '38240'
year: '2021'
...
---
_id: '10780'
author:
- first_name: Zakarya
full_name: Guettatfi, Zakarya
last_name: Guettatfi
- first_name: Philipp
full_name: Hübner, Philipp
last_name: Hübner
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
- first_name: Bernhard
full_name: Rinner, Bernhard
last_name: Rinner
citation:
ama: 'Guettatfi Z, Hübner P, Platzner M, Rinner B. Computational self-awareness
as design approach for visual sensor nodes. In: 12th International Symposium
on Reconfigurable Communication-Centric Systems-on-Chip (ReCoSoC). ; 2017:1-8.
doi:10.1109/ReCoSoC.2017.8016147'
apa: Guettatfi, Z., Hübner, P., Platzner, M., & Rinner, B. (2017). Computational
self-awareness as design approach for visual sensor nodes. In 12th International
Symposium on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC)
(pp. 1–8). https://doi.org/10.1109/ReCoSoC.2017.8016147
bibtex: '@inproceedings{Guettatfi_Hübner_Platzner_Rinner_2017, title={Computational
self-awareness as design approach for visual sensor nodes}, DOI={10.1109/ReCoSoC.2017.8016147},
booktitle={12th International Symposium on Reconfigurable Communication-centric
Systems-on-Chip (ReCoSoC)}, author={Guettatfi, Zakarya and Hübner, Philipp and
Platzner, Marco and Rinner, Bernhard}, year={2017}, pages={1–8} }'
chicago: Guettatfi, Zakarya, Philipp Hübner, Marco Platzner, and Bernhard Rinner.
“Computational Self-Awareness as Design Approach for Visual Sensor Nodes.” In
12th International Symposium on Reconfigurable Communication-Centric Systems-on-Chip
(ReCoSoC), 1–8, 2017. https://doi.org/10.1109/ReCoSoC.2017.8016147.
ieee: Z. Guettatfi, P. Hübner, M. Platzner, and B. Rinner, “Computational self-awareness
as design approach for visual sensor nodes,” in 12th International Symposium
on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC), 2017, pp.
1–8.
mla: Guettatfi, Zakarya, et al. “Computational Self-Awareness as Design Approach
for Visual Sensor Nodes.” 12th International Symposium on Reconfigurable Communication-Centric
Systems-on-Chip (ReCoSoC), 2017, pp. 1–8, doi:10.1109/ReCoSoC.2017.8016147.
short: 'Z. Guettatfi, P. Hübner, M. Platzner, B. Rinner, in: 12th International
Symposium on Reconfigurable Communication-Centric Systems-on-Chip (ReCoSoC), 2017,
pp. 1–8.'
date_created: 2019-07-10T12:13:15Z
date_updated: 2022-01-06T06:50:50Z
department:
- _id: '78'
doi: 10.1109/ReCoSoC.2017.8016147
keyword:
- embedded systems
- image sensors
- power aware computing
- wireless sensor networks
- Zynq-based VSN node prototype
- computational self-awareness
- design approach
- platform levels
- power consumption
- visual sensor networks
- visual sensor nodes
- Cameras
- Hardware
- Middleware
- Multicore processing
- Operating systems
- Runtime
- Reconfigurable platforms
- distributed embedded systems
- performance-resource trade-off
- self-awareness
- visual sensor nodes
language:
- iso: eng
page: 1-8
publication: 12th International Symposium on Reconfigurable Communication-centric
Systems-on-Chip (ReCoSoC)
status: public
title: Computational self-awareness as design approach for visual sensor nodes
type: conference
user_id: '3118'
year: '2017'
...
---
_id: '11892'
abstract:
- lang: eng
text: For an environment to be perceived as being smart, contextual information
has to be gathered to adapt the system's behavior and its interface towards the
user. Being a rich source of context information speech can be acquired unobtrusively
by microphone arrays and then processed to extract information about the user
and his environment. In this paper, a system for joint temporal segmentation,
speaker localization, and identification is presented, which is supported by face
identification from video data obtained from a steerable camera. Special attention
is paid to latency aspects and online processing capabilities, as they are important
for the application under investigation, namely ambient communication. It describes
the vision of terminal-less, session-less and multi-modal telecommunication with
remote partners, where the user can move freely within his home while the communication
follows him. The speaker diarization serves as a context source, which has been
integrated in a service-oriented middleware architecture and provided to the application
to select the most appropriate I/O device and to steer the camera towards the
speaker during ambient communication.
author:
- first_name: Joerg
full_name: Schmalenstroeer, Joerg
id: '460'
last_name: Schmalenstroeer
- first_name: Reinhold
full_name: Haeb-Umbach, Reinhold
id: '242'
last_name: Haeb-Umbach
citation:
ama: Schmalenstroeer J, Haeb-Umbach R. Online Diarization of Streaming Audio-Visual
Data for Smart Environments. IEEE Journal of Selected Topics in Signal Processing.
2010;4(5):845-856. doi:10.1109/JSTSP.2010.2050519
apa: Schmalenstroeer, J., & Haeb-Umbach, R. (2010). Online Diarization of Streaming
Audio-Visual Data for Smart Environments. IEEE Journal of Selected Topics in
Signal Processing, 4(5), 845–856. https://doi.org/10.1109/JSTSP.2010.2050519
bibtex: '@article{Schmalenstroeer_Haeb-Umbach_2010, title={Online Diarization of
Streaming Audio-Visual Data for Smart Environments}, volume={4}, DOI={10.1109/JSTSP.2010.2050519},
number={5}, journal={IEEE Journal of Selected Topics in Signal Processing}, author={Schmalenstroeer,
Joerg and Haeb-Umbach, Reinhold}, year={2010}, pages={845–856} }'
chicago: 'Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Online Diarization
of Streaming Audio-Visual Data for Smart Environments.” IEEE Journal of Selected
Topics in Signal Processing 4, no. 5 (2010): 845–56. https://doi.org/10.1109/JSTSP.2010.2050519.'
ieee: 'J. Schmalenstroeer and R. Haeb-Umbach, “Online Diarization of Streaming Audio-Visual
Data for Smart Environments,” IEEE Journal of Selected Topics in Signal Processing,
vol. 4, no. 5, pp. 845–856, 2010, doi: 10.1109/JSTSP.2010.2050519.'
mla: Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Online Diarization of Streaming
Audio-Visual Data for Smart Environments.” IEEE Journal of Selected Topics
in Signal Processing, vol. 4, no. 5, 2010, pp. 845–56, doi:10.1109/JSTSP.2010.2050519.
short: J. Schmalenstroeer, R. Haeb-Umbach, IEEE Journal of Selected Topics in Signal
Processing 4 (2010) 845–856.
date_created: 2019-07-12T05:30:16Z
date_updated: 2023-10-26T08:10:18Z
department:
- _id: '54'
doi: 10.1109/JSTSP.2010.2050519
intvolume: ' 4'
issue: '5'
keyword:
- audio streaming
- audio visual data streaming
- context information speech
- face identification
- face recognition
- image segmentation
- middleware
- multimodal telecommunication
- online diarization
- service oriented middleware architecture
- sessionless telecommunication
- software architecture
- speaker identification
- speaker localization
- speaker recognition
- steerable camera
- telecommunication computing
- temporal segmentation
- terminal-less telecommunication
- video streaming
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://groups.uni-paderborn.de/nt/pubs/2010/ScHa10.pdf
oa: '1'
page: 845-856
publication: IEEE Journal of Selected Topics in Signal Processing
quality_controlled: '1'
status: public
title: Online Diarization of Streaming Audio-Visual Data for Smart Environments
type: journal_article
user_id: '460'
volume: 4
year: '2010'
...
---
_id: '6094'
abstract:
- lang: eng
text: In the current study, we tested whether search for a visual motion singleton
presented among several coherently moving distractors can be more efficient than
search for a motion stimulus presented with a single distractor. Under a variety
of conditions, multiple spatially distributed and coherently moving distractors
facilitated search for a uniquely moving target relative to a single-motion-distractor
condition (Experiments 1,3, and 4). Color coherencies among static distractors
were not equally effective (Experiments 1 and 2). These results confirm that humans
are highly sensitive to antagonistically directed motion signals in backgrounds
compared with spatially more confined regions of visual images. (PsycINFO Database
Record (c) 2016 APA, all rights reserved)
author:
- first_name: Ulrich
full_name: Ansorge, Ulrich
last_name: Ansorge
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
- first_name: Kirsten
full_name: Labudda, Kirsten
last_name: Labudda
citation:
ama: Ansorge U, Scharlau I, Labudda K. Visual search for a motion singleton among
coherently moving distractors. Psychological Research. 2006;70(2):103-116.
apa: Ansorge, U., Scharlau, I., & Labudda, K. (2006). Visual search for a motion
singleton among coherently moving distractors. Psychological Research,
70(2), 103–116.
bibtex: '@article{Ansorge_Scharlau_Labudda_2006, title={Visual search for a motion
singleton among coherently moving distractors.}, volume={70}, number={2}, journal={Psychological
Research}, author={Ansorge, Ulrich and Scharlau, Ingrid and Labudda, Kirsten},
year={2006}, pages={103–116} }'
chicago: 'Ansorge, Ulrich, Ingrid Scharlau, and Kirsten Labudda. “Visual Search
for a Motion Singleton among Coherently Moving Distractors.” Psychological
Research 70, no. 2 (2006): 103–16.'
ieee: U. Ansorge, I. Scharlau, and K. Labudda, “Visual search for a motion singleton
among coherently moving distractors.,” Psychological Research, vol. 70,
no. 2, pp. 103–116, 2006.
mla: Ansorge, Ulrich, et al. “Visual Search for a Motion Singleton among Coherently
Moving Distractors.” Psychological Research, vol. 70, no. 2, 2006, pp.
103–16.
short: U. Ansorge, I. Scharlau, K. Labudda, Psychological Research 70 (2006) 103–116.
date_created: 2018-12-10T07:08:57Z
date_updated: 2022-06-07T00:21:31Z
department:
- _id: '424'
extern: '1'
intvolume: ' 70'
issue: '2'
keyword:
- visual search
- motion singleton
- visual images
- visual motion
- coherently moving distractors
- Adult
- Attention
- Exploratory Behavior
- Female
- Humans
- Male
- Motion Perception
- Visual Perception
- Motion Perception
- Stimulus Salience
- Visual Search
- Distraction
- Retinal Image
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://kw.uni-paderborn.de/fileadmin/fakultaet/Institute/psychologie/Kognitive_Psychologie/Publikationen/AnsorgeScharlauLabudda.pdf
oa: '1'
page: 103 - 116
publication: Psychological Research
publication_identifier:
issn:
- 0340-0727
publication_status: published
status: public
title: Visual search for a motion singleton among coherently moving distractors.
type: journal_article
user_id: '42165'
volume: 70
year: '2006'
...