In the Transformationally Invariant KInematics (TIKi) lab we integrate knowledge and methods from Psychology and Informatics, with particular emphasis on perception and computer graphics. In particular, we combine low-level psychophysics with modern computer graphics to allow an ecological psychology approach to modeling and synthesizing behaviorally relevant, spatiotemporal information.

Although visual scenes contain an enormous amount of information, humans and computers have only a limited amount of resources to extract, represent, manipulate, and use that information. Although psychology and computer science have separately approached the issue of how a system, either synthetic or organic, might accomplish these tasks, a synergistic fusion of the methods and knowledge of these two fields can provide innovative and efficient solutions. For example, knowledge about motion processing, stereopsis, and compensation for internal noise can provide insights into how computer graphics and computer vision might deal with similar problems. Likewise, knowledge about the dimensions and features that are important for more cognitive human abilities can be useful in the design of algorithms for similar domains (e.g., expert systems, visualization). Computer science techniques for solving these problems, on the other hand, can be used as potential models for human mechanisms.

This website uses cookies. There are two types of cookies: The first type supports the basic functionality of our website. The second allows us to improve our content for you by saving and analyzing pseudonymised user data. Since this second type is technically not required to run the website, you can withdraw your consent to those cookies at any time. For more information please visit our pages on data protection.


These cookies are needed for a smooth operation of our website.


For statistical reasons, we use the platform Matomo to analyse the user flow with the help of website users‘ pseudonymised data. This allows us to optimize website content.

Name Purpose Lifetime Type Provider
_pk_id Used to store a few details about the user such as the unique visitor ID. 13 months HTML Matomo
_pk_ref Used to store the attribution information, the referrer initially used to visit the website. 6 months HTML Matomo
_pk_ses Short lived cookie used to temporarily store data for the visit. 30 minutes HTML Matomo