Difference between revisions of "Faces"
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'''NOTE: This page is currently under construction. Please don't edit it at the moment!''' | |||
FACES is a collaboration of the MPDL with the Max Planck Institute for Human Developement. | FACES is a collaboration of the MPDL with the Max Planck Institute for Human Developement. | ||
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* JPG Images | * JPG Images | ||
* Attribute Export as CSV | * Attribute Export as CSV | ||
* No standard metadata-profiles involved | * No standard metadata-profiles involved | ||
'''Available Image Resolutions''' | '''Available Image Resolutions''' | ||
Revision as of 08:24, 28 June 2007
NOTE: This page is currently under construction. Please don't edit it at the moment!
FACES is a collaboration of the MPDL with the Max Planck Institute for Human Developement.
What is FACES[edit]
Overview[edit]
FACES is a lifespan database of adult emotional facial stimuli. It contains a set of images of naturalistic faces of 171 persons, seperated in three different age groups (young, middle-aged and old) displaying each of 6 facial expressions: neutrality, sadness, disgust, fear, anger, and happiness.
For more details, please visit the FACES database homepage.
Details[edit]
Scope
- Developed between 2005-2007
- Currently 171 persons (men and women)
- 2 x 6 emotions
- 2052 pictures overall
- Available to defined user-group only as a java-application to be ordered by request on CD
Current Attributes
- ID, age, gender, emotion, picture group
Current Emotions
- Neutrality, sadness, disgust, fear, anger, happiness
Current Age Groups
- Young (58 persons), middle-aged (56 persons), old (n=persons)
Formats
- JPG Images
- Attribute Export as CSV
- No standard metadata-profiles involved
Available Image Resolutions
- 819 x 1024
- 2835 x 3543
- Thumbnails to be generated automatically
What should FACES become[edit]
Aim of the collaboration (expressed by UF):
Wesentlich wird es – neben der Einbindung in die eSciDoc-Architektur – darum gehen, die bisherigen "Attribute" auf der Ebene des einzelnen Bildes zu ergänzen um weitere, standardisierte Metadaten (ggf. METS) , und ein Rechtemanagement zu implementieren, d.h. differenzierte Zugriffsrechte zu ermöglichen. Dabei muss die Datenbank strukturell offen sein für die Aufnahme weiterer (Beschreibungs-) Daten – wie etwa von der Normierungsstudie zu erwarten.
NEW Additional example ratings coming up from the normstudy:
- Attractiveness, age, distinctiveness, goal orientation, type of emotion perceived
Administration
- Importing of Pictures
- Adding of Attributes to Images, also from External Data
Viewer
- Browse Photo Collection
- View Photos and their attributes
- Select subset of Photos according to their attributes
- Manually refine selection
- Export result set including attribute data