Christian Wallraven 교수

Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support vector machines have been established as powerful learning algorithms with good generalization capabilities. We combine these two approaches and propose a general kernel method for recognition with local features. We show that the proposed kernel satisfies the Mercer condition and that it is, suitable for many established local feature framew

The ability to communicate is one of the core aspects of human life. For this, we use not only verbal but also nonverbal signals of remarkable complexity. Among the latter, facial expressions belong to the most important information channels. Despite the large variety of facial expressions we use in daily life, research on facial expressions has so far mostly focused on the emotional aspect. Consequently, most databases of facial expressions available to the research community also include only

Communication is critical for normal, everyday life. During a conversation, information is conveyed in a number of ways, including through body, head, and facial changes. While much research has examined these latter forms of communication, the majority of it has focused on static representations of a few, supposedly universal expressions. Normal conversations, however, contain a very wide variety of expressions and are rarely, if ever, static. Here, we report several experiments that show that

The human face is capable of producing an astonishing variety of expressions—expressions for which sometimes the smallest difference changes the perceived meaning considerably. Producing realistic-looking facial animations that are able to transmit this degree of complexity continues to be a challenging research topic in computer graphics. One important question that remains to be answered is: When are facial animations good enough? Here we present an integrated framework in which psychophysical

Primates possess the remarkable ability to differentiate faces of group members and to extract relevant information about the individual directly from the face. Recognition of conspecific faces is achieved by means of holistic processing, i.e. the processing of the face as an unparsed, perceptual whole, rather than as the collection of independent features (part-based processing). The most striking example of holistic processing is the Thatcher illusion. Local changes in facial features are hard

Even though we can recognize faces by touch surprisingly well, haptic face recognition performance is still worse than for visual exploration. One possibility for this performance difference might be due to different encoding strategies in the two modalities, namely, holistic encoding in vision versus serial encoding in haptics. Here, we tested this hypothesis by promoting serial encoding in vision, using a novel, gaze-restricted display that limited the effective field of view in vision to rese

The goal of stylization is to provide an abstracted representation of an image that highlights specific types of visual information. Recent advances in computer graphics techniques have made it possible to render many varieties of stylized imagery efficiently making stylization into a useful technique, not only for artistic, but also for visualization applications. In this paper, we report results from two sets of experiments that aim at characterizing the perceptual impact and effectiveness of

A "masked face", that is, decreased facial expression is considered as one of the cardinal symptoms among individuals with Parkinson's disease (PD). Both spontaneous and voluntary mimicry toward others' emotional expressions is essential for both social communication and emotional sharing with others. Despite many studies showing impairments in facial movements in PD in general, it is still unclear whether voluntary, spontaneous, or both types of mimicry are affected and how the impairments affe

By looking at a work of art, an observer enters into a dialogue. In this work, we attempt to analyze this dialogue with both behavioral and computational tools. In two experiments, observers were asked to look at a large number of paintings from different art periods and to rate their visual complexity, or their aesthetic appeal. During these two tasks, their eye movements were recorded. The complexity and aesthetic ratings show clear preferences for certain artistic styles and were based on bot

We present an exemplar-based object recognition system which is capable of on-line learning of representations of scenes and objects from image sequences. Local appearance features are used in a tracking framework to find `key-frames' of the input sequence during learning. The representation of the stored sequences which are used for recognition of novel images consists only of the appearance features in these key-frames and contains no further a-priori assumptions about the underlying sequences

The human face is capable of producing an astonishing variety of expressions---expressions for which sometimes the smallest difference changes the perceived meaning noticably. Producing realistic-looking facial animations that are able to transport this degree of complexity continues to be a challenging research topic in computer graphics. One important question that remains to be answered is: When are facial animations good enough? Here we present an integrated framework in which psychophysical