Learn More
This paper deals with the fully automatic extraction of classifiable person features out of a video stream with challenging background. Basically the task can be split in two parts: Tracking the object and extracting distinctive features. In order to track a person, a system composed of an active shape model embedded in a particle filter framework has been(More)
Non-rigid registration of 3D facial surfaces is a crucial step in a variety of applications. Outliers, i.e., features in a facial surface that are not present in the reference face, often perturb the registration process. In this paper, we present a novel method which registers facial surfaces reliably also in the presence of huge outlier regions. A cost(More)
Active Appearance Models (AAMs) can be used for interpreting face images and image sequences. AAMs combine a statistical shape model and a model of grey-level appearance. They also contain an iterative matching scheme for image interpretation, which only needs an initial estimate of the position and size of the face and results in a set of parameters(More)
Using standard background modeling approaches, close or overlapping objects are often detected as a single blob. In this paper we propose a new and effective method to distinguish between overlapping foreground objects in data obtained from a time of flight sensor. For this we use fusion of the infrared and the range data channels. In addition a further(More)
Face recognition in range images is a challenging task, especially if the pose of the shown face is unknown. To solve this, an alignment procedure consisting of facial feature hypotheses extraction by invariant curvature features, PCA-based classification and Iterative Closest Point alignment will be introduced to create aligned and normalized patches.(More)
In this paper a view-independent head tracking system applying an Active Shape Model based particle filter is used to find precise image sections. DCTmod2 feature sequences are extracted from these sections and given as input to Cyclic Pseudo two-dimensional Hidden Markov Model based classifiers. These classifiers are trained to recognize the identity of(More)
Unconstrained face recognition is the problem of deciding if an image pair is showing the same individual or not, without having class specific training material or knowing anything about the image conditions. In this paper, an approach of learning suited similarity measurements is introduced. For this the image is partitioned into several parts, to extract(More)
hunderts), bespricht das Wesen derselben, zeigt, welche Elemente Nebenvalenzen gegeneinander entfal ten and in welcher Zahl and teilt schlieBlich die Verbindungen mit Neben'calenzen in folgender Weise ein : L Klasse. Nebenvalenzen "con Atomen, die ihre Hauptvalenzen ganz oder teilweise abges~ittigt haben. 1. Gruppe. Die Vereinigung "con zwei oder mehreren(More)
  • 1