Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
  Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben
Konferenzbeitrag

Impact of Reviewing Lifelogging Photos on Recalling Episodic Memories

MPG-Autoren
/persons/resource/persons84065

Machulla,  T
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

Externe Ressourcen

Link
(beliebiger Volltext)

Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

El.Agroudy, P., Machulla, T., Rzayev, R., Dingler, T., Funk, M., Schmidt, A., et al. (2016). Impact of Reviewing Lifelogging Photos on Recalling Episodic Memories. In P. Lukowicz, & A. Krüger (Eds.), ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '16) (pp. 1014-1019). New York, NY, USA: ACM Press.


Zitierlink: https://hdl.handle.net/21.11116/0000-0000-7A76-3
Zusammenfassung
Photos are a rich and popular form for preserving memories.
Thus, they are widely used as cues to augment human
memory. Near-continuous capture and sharing of photos
have generated a need to summarize and review relevant
photos to revive important events. However, there is limited
work on exploring how regular reviewing of selected photos
influence overall recall of past events. In this paper, we
present an experiment to investigate the effect of regular
reviewing of egocentric lifelogging photos on the formation
and retrieval of autobiographic memories. Our approach
protects the privacy of the participants and provides improved validation for their memory performance compared
to existing approaches. The results of our experiment are
a step towards developing memory shaping algorithms that
accentuate or attenuate memories on demand.