Group leader

 Dr. Isabelle Bülthoff
Phone: +49 7071 601-611
Fax: +49 7071 601-616

RecCat Overview Poster

Five most recent publications

Janssen CP, Boyle LN, Kun AL, Ju W and Chuang L (July-2018) A Hidden Markov Framework to Capture Human-Machine Interaction in Automated Vehicles International Journal of Human-Computer Interaction . in press
Danyeli L, Alizadeh S, Surova G, Jamalabadi H, Schultz M and Walter M (June-2017): Effects of Neurexan® on brain responses to deviant stimuli during an auditory oddball task, ISAD LONDON 2017: Perspectives on Mood and Anxiety Disorders: Looking to the future, London, UK, Frontiers in Psychiatry, Conference Abstracts: ISAD LONDON 2017.
Bülthoff I (November-9-2015) Invited Lecture: Race and identity: what gives a face its race and what do we remember about familiar faces?, University Bremen: Cognium, Bremen, Germany.
Chuang LL (November-5-2015) Invited Lecture: Beyond Steering in Human-Centered Closed-Loop Control, Institute for Neural Computation: INC Chalk Talk Series, San Diego, CA, USA.
Stangl M, Meilinger T, Pape A-A, Schultz J, Bülthoff HH and Wolbers T (October-19-2015): Triggers of entorhinal grid cell and hippocampal place cell remapping in humans, 45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), Chicago, IL, USA.

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All RecCat publications

For all publications by RecCat members, click here


Recognition and Categorization

This office scene illustrates many of the problems encountered when we recognize and categorize objects. For example, we recognize all chairs easily, although they are seen from different orientations and although some of them are partially occluded.
We can easily recognize and categorize objects at different levels depending on task requirements. An animal can be recognized as belonging to a category such as “a dog” (categorization) or as “my dog Bashi” (identification). Among all categories of objects, faces constitute a very special class because of their social importance and their high intra-group similarity. Therefore, the RECCAT group mainly focuses on the perception of faces, with an added interest for the perception of human bodies and other objects



The long-standing goal of our group is to unravel the mechanisms underlying recognition and categorization of faces, bodies and objects.
Our research focuses on three main aspects:
(1) To investigate recognition and categorization not only in traditional settings (static images shown on a computer screen) but also in more naturalistic scenarios where faces and human figures are moving or where the observers are actively exploring virtual environments.
(2) To investigate perception in other populations, such as those with different cultural backgrounds (e.g. Koreans) or lacking specific skills (e.g. prosopagnosics), and more generally to investigate the role of expertise and cultural background in face recognition.
(3) To investigate the brain processes involved when we recognize or categorize faces, bodies or object surfaces.

Main research areas

Here we present some recent and on-going projects that illustrate five of our research directions.

1. Perceiving static and animated faces and bodies:

  • Visual periphery plays a more important role in daily life than merely triggering gaze saccades to events in our environment [Opens internal link in current windowFademrecht].

We used life-size animated and static human avatars to investigate action recognition in central and far peripheral vision.  Our results have shown that action recognition remains extremely accurate, even for actions presented far away from fixation. In sum, our studies have revealed that the recognition abilities of peripheral vision have been underestimate.

  • Moving faces are processed holistically [Opens internal link in current windowZhao & Bülthoff].
Holistic processing denotes the tendency to perceive objects as indecomposable wholes. We tested participants for holistic processing with static and moving faces. Their responses demonstrate that both types of faces are perceived holistically.
  • Active exploration of avatars in virtual reality and its concomitant dynamic experience of the faces to be remembered leads to enhanced face recognition [Opens internal link in current windowBülthoff et al].
We tested face recognition performance of active and passive participants. The active participants explored a virtual room filled with avatars, while passive participants viewed dynamic or static renditions of these explorations. Active participants and passive participants viewing dynamic renderings of the faces to learn displayed more robust face recognition.

2. Multisensory representation of persons

  • Distinctive (out of the ordinary) voices can prime the recognition of their paired faces better than typical (ordinary) voices [Opens internal link in current windowBülthoff & Newell].
We paired ordinary faces to distinctive and ordinary voices or sounds during a learning session. Afterwards, priming was found for voices, but not for sounds and the best primes were distinctive voices. Our findings suggest an early and specific convergence of voices and faces in multisensory representation of persons.

3. Holistic processing of faces, bodies and objects

  • Static faces and line patterns are perceived holistically [Opens internal link in current windowZhao et al]
Holistic processing—the tendency to perceive objects as indecomposable wholes—has long been viewed as a process specific to faces or objects of expertise. Our experiments show that unknown line patterns are processed as holistically as faces without any training.
  • Are faces, objects and bodies processed holistically in common brain areas? [Opens internal link in current windowFoster et al]
We used visual stimuli that consisted of faces, line patterns and bodies in a typical task testing for holistic processing (the full composite task). The brain activity of participants was recorded while they performed this task. Region of interest and whole-brain analyses will be used to find out whether there are common holistically-involved areas activated during this task.

4. Perception of familiar and unfamiliar faces

  • Not all aspects of very familiar faces are represented equally precisely [Opens internal link in current windowBülthoff & Zhao]
We modified personally familiar faces to investigate what aspects of familiar faces we remember best. Modifications of the race and sex of familiar faces were not as easily discriminated as modifications related to the identity of a face.

5. Tactile perception

  • Neural representations of perceived roughness [Opens internal link in current windowKim et al]
Surfaces with five levels of roughness were presented to participants visually, tactilely or both while their brain activity was recorded. Multi-voxel pattern analysis shows that roughness intensity information could be decoded independent to the stimulus types. 

Methods and Stimuli

Some of the stimuli used in our projects. A: Line patterns and faces in a composite task. B: Face and bodies used in brain imaging. C: Virtual environment. D: Original face A and morphs of that face mixed with either person B or person C. E: Various surface stimuli were probed with the hand to investigate tactile perception.
In addition to classical psychophysical techniques, we use functional brain imaging[Siemens 3T at Magnetic Resonance Center] and eye tracking methods to investigate the processes underlying recognition and categorization. In the projects of the group, the use of moving stimuli (dynamic faces can be recorded or created using the MPI VideoLab) and/or the combination of classical psychophysical techniques with virtual reality setups using both body-tracking technology (VICON MX), immersive head-mounted visual displays and large screens allow for more naturalistic test environment.


Collaborations within the Department
Betty Mohler (Opens internal link in current windowSpace and Body Perception)
Stephan de la Rosa (Opens internal link in current windowSocial and Spatial Cognition)

External Academic Collaborations

Opens external link in new windowMichael Black (Perceiving Systems Department, MPI for intelligent systems),
Opens external link in new windowAndreas Bartels (Werner Reichardt Centre for Integrative Neuroscience)
Wallraven (Korea), Ian M Thornton (UK), Quoc Vuong (UK), Opens external link in new windowNewell (Ireland), Opens external link in new windowSung-Phil Kim (Korea)


For a full list of publications by RecCat members, click here

Selected publications: Articles 2009-present

Bieg H-J, Bresciani J-P, Bülthoff HH and Chuang LL (September-2012) Looking for Discriminating Is Different from Looking for Looking's Sake PLoS ONE 7(9) 1-9.
Gaissert N, Waterkamp S, Fleming RW and Bülthoff I (August-2012) Haptic Categorical Perception of Shape PLoS One 7(8) 1-7.
Bülthoff I (July-2012) Review: L'empreinte Des Sens Perception 41(7) 881-882.
Armann R and Bülthoff I (June-2012) Male and female faces are only perceived categorically when linked to familiar identities – And when in doubt, he is a male Vision Research 63 69-80.
Chuang LL, Vuong QC and Bülthoff HH (May-2012) Learned non-rigid object motion is a view-invariant cue to recognizing novel objects Frontiers in Computational Neuroscience 6(26) 1-8.
Helbig HB, Ernst MO, Ricciardi E, Pietrini P, Thielscher A, Mayer KM, Schultz J and Noppeney U (April-2012) The neural mechanisms of reliability weighted integration of shape information from vision and touch NeuroImage 60(2) 1063–1072.
Kaulard K, Cunningham DW, Bülthoff HH and Wallraven C (March-2012) The MPI Facial Expression Database: A Validated Database of Emotional and Conversational Facial Expressions PLoS One 7(3) 1-18.
Gaissert N and Wallraven C (January-2012) Categorizing natural objects: a comparison of the visual and the haptic modalities Experimental Brain Research 216(1) 123-134.
Dopjans L, Bülthoff HH and Wallraven C (January-2012) Serial exploration of faces: Comparing vision and touch Journal of Vision 12(1:6) 1-14.
Armann R, Jeffery L, Calder AJ and Rhodes G (November-2011) Race-specific norms for coding face identity and a functional role for norms Journal of Vision 11(13:9) 1-14.
Bülthoff HH and Chuang LL (September-2011) Seeing: The Computational Approach to Biological Vision. Second Edition. By John P. Frisby and James V. Stone. Cambridge (Massachusetts): MIT Press Quarterly Review of Biology 86(3) 227.
Gaissert N, Bülthoff HH and Wallraven C (September-2011) Similarity and categorization: From vision to touch Acta Psychologica 138(1) 219-230.
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Last updated: Friday, 23.02.2018