InterFace : A software package for face image warping, averaging, and principal components analysis

We describe InterFace, a software package for research in face recognition. The package supports image warping, reshaping, averaging of multiple face images, and morphing between faces. It also supports principal components analysis (PCA) of face images, along with tools for exploring the “face space” produced by PCA. The package uses a simple graphical user interface, allowing users to perform these sophisticated image manipulations without any need for programming knowledge. The program is available for download in the form of an app, which requires that users also have access to the (freely available) MATLAB Runtime environment

Influence of varied human movement control on task performance and feeling of telepresence

One of the main objectives in telerobotics is the development of a telemanipulation system that allows a high task performance to be achieved by simultaneously providing a high degree of telepresence. Specific mechatronic design guidelines and appropriate control algorithms as well as augmented visual, auditory, and haptic feedback systems are typical approaches adopted in this context. This work aims at formulating new design guidelines by incorporating human factors in the development process and analyzing the effects of varied human movement control on task performance and on the feeling of telepresence. While it is well known that humans are able to coordinate and integrate multiple degrees of freedom (DOF), the focus of this work is on how humans utilize rotational degrees of freedom provided by a human-system interface and if and how varied human movement control affects task performance and the feeling of telepresence. For this analysis, a telemanipulation experiment with varying degrees of freedom has been conducted. The results indicate that providing the full range of movement, even though this range is not necessary to accomplish a task, has a beneficial effect on the feeling of telepresence and task performance in terms of measured interaction forces. Further, increasing visual depth cues provided to the human operator also had a positive effect. © 2010 by the Massachusetts Institute of Technology

Non Linear, Near Photo-Realistic Caricatures using a Parametric Facial Appearance Model

A mathematical model previously developed for use in computer vision applications is presented as an empirical model for face space. The term appearance space is used to distinguish this from previous models. Appearance space is a linear vector space that is dimensionally optimal, enables us to model and describe any human facial appearance, and possesses characteristics that are plausible for the representation of psychological face space. Randomly sampling from a multivariate distribution for a location in appearance space produces entirely plausible faces, and manipulation of a small set of defining parameters enables the automatic generation of photo-realistic caricatures. The appearance space model leads us to the new concept of nonlinear caricatures, and we show that the accepted linear method for caricature is only a special case of a more general paradigm. Nonlinear methods are also viable, and we present examples of photographic quality caricatures, using a number of different transformation functions. Results of a simple experiment are presented that suggest that nonlinear transformations can accurately capture key aspects of the caricature effect. Finally, we discuss the relationship between appearance space, caricature, and facial distinctiveness. On the basis of our new theoretical framework, we suggest an experimental approach that can yield new evidence for the plausibility of face space and its ability to explain processes of recognition