Group Recognition and Categorization
I lead the group of the department .
My research concerns human face recognition. To that end, I use primarily psychophysical methods, eye-tracking, immersive virtual environments and face images derived from our face database.
Faces are the most fascinating objects for human beings. We are never tired of looking at faces, a fact used heavily by advertising companies. In the course of our childhood, we develop a remarkable expertise at deciphering the most subtle aspects of a face, not only do we recognize identity or sex, but we also notice, for example, signs of tiredness, sadness or age.
While we are expert in face recognition in general, we process and retrieve information about familiar and unfamiliar faces differently. We use preferably the inner features for recognizing familiar faces, while for unfamiliar faces we pay more attention to and keep in memory more likely extra-facial information like hairdo, glasses or beards. In one project, I investigate the recognition of personally familiar faces, as they are the faces that we remember best. With these faces, we can test how precisely facial information related to sex, race or identity is memorized. I concentrate on those aspects of faces, as we use those attributes most osten to describe or classify faces. Our results give insight about how very familiar faces are represented in memory. They reveal that facial information regarding sex and race are represented only very coarsely in memory, while those linked to identity are encoded very precisely.
Another line of study (in collaboration with the group) uses the advantages of virtual reality to investigate face recognition under more natural conditions. Most studies so far tested isolated static faces. In our project, observers moved physically in a virtual room to look at the faces of life-size avatars. We compared the recognition performance of this active group to that of other groups with different learning conditions. Overall, the active group performed better than the other groups.
In collaboration with , and other colleagues, additional projects investigate, among others, holistic processing of faces, the other-race effect and the influence of voices on face recognition.
Projects in collaboration with PhD students of the presently include:
- : Neural coding of Features shared by faces, bodies & objects. Her work is co-supervised by , so as and .
- What gives a face its ethnicity? We can quickly and easily judge faces in terms of their ethnicity. In a series of studies, we investigate whether one or another part of the face (eyes, mouth ) has more influence on perceived ethnicity of that face. This work is done in collaboration with Korea University (in the ) and involves participants of different cultural background and expertise in terms of face ethnicities.
- Influence of body size on face recognition. The concept of Embodied Cognition implies that our own bodies, the way we act with our bodies, and the way our bodies fit into the environment, should all have important implications for our mental representation of the world. Thus the question arises whether we represent and/or process faces in a different way depending on our body size. This work is done in collaboration with (University of Malta, Malta) and .
Current project in more details:
Personally familiar faces: Higher precision of memory for idiosyncratic than for sex or race facial information
We process and retrieve information about familiar and unfamiliar faces differently. We use preferably the inner features for recognizing familiar faces, while for unfamiliar faces we keep in memory more likely extra-facial information like hairdo, glasses or beards1. Testing memory of very familiar faces allows us to test how precisely different types of facial information are memorized.
We investigate whether facial information related to either sex, race or identity might be remembered more precisely than the others. We concentrate on those aspects, as they represent some attributes that we use most commonly to describe or classify faces. The results will give insight about how very familiar faces are represented.
The faces of members of the department were used as personally familiar test faces and the members of the department were our participants. The veridical faces were manipulated2 in increasing manner in four different ways: they were (1) morphed with other identities, (2) caricatured and anti-caricatured, (3) made more feminine looking and more masculine looking and (4) made more Caucasian looking and more Asian looking. In each test trial, a veridical face was shown with its distracters (the faces obtained with one of the four manipulations). Participants had to find the veridical face among the distracters.
Figure 1 shows that participants chose the veridical face most frequently when the distracters were identity morphs, while this was not the case for the other manipulations.
Our results reveal that for personally familiar faces, their facial information regarding sex and race are represented only very coarsely in memory, while those linked to identity are encoded very precisely.
Left: Mean choice frequency for veridical faces and their identity morphs. Right: Mean choice frequency for veridical faces and their race morphs. Stars denote values differing significantly from chance level.
1. Johnston, R. A., & Edmonds, A. J. (2009). Familiar and unfamiliar face recognition: A review. Memory, 17(5), 577596.
2. Blanz, V., & Vetter, T. (1999). A morphable model for the synthesis of 3D faces. In Proceedings of the 26th annual conference on Computer graphics and interactive techniques - SIGGRAPH 99 (pp. 187194). New York, New York, USA: ACM Press.
1979 Licence ès Sciences naturelles (equivalent to MA in natural Sciences in the US), University of Lausanne, Switzerland.
1983 Ph.D in Zoology, University of Lausanne, Switzerland. Doctoral Dissertation accomplished at the Max-Planck institute for Biological Cybernetics, Tübingen, Germany.
Academic and Research Experience
1977-1978 Teaching assistant in Zoology, University of Lausanne, Switzerland
1979-1983 Doctoral work. Doctoral Dissertation: Visual mutants of Drosophila melanogaster, functional neuroanatomical mapping of nervous activity by 3H-Deoxyglucose method. Max-Planck institute for Biological Cybernetics, Tübingen, Germany
1983-1885 Postdoctoral fellow, Max-Planck-Institut für biologische Kybernetik, Tübingen, Germany, funded by the Swiss Research Foundation
1986-1991 Child rearing period (2 children)
1991-1993 Research assistant, Neuroscience Department, (Prof. Barry Connors), Brown University, RI, USA
Since 09/1993 Researcher at the Max-Planck-Institut für biologische Kybernetik, Tübingen, Germany
Since 01/2009 Project leader at the Max-Planck-Institut für biologische Kybernetik, Tübingen, Germany
Major Research Interests
Investigating the mechanisms underlying face recognition. At present my focus is on the following themes:
- The interplay between gender and identity information in face recognition
- The impact of voice distinctiveness on face recognition
- The influence of context and task on face recognition
- Crosscultural differences in face and object recognition
- The role of idiosyncratic viewing history in face recognition