This paper describes a new technique for statistical 3{D object localization. Local feature vectors are extracted for all image positions, in contrast to seg-mentation in classical schemes. We deene a density function for those features and describe a hierarchical pose estimation scheme for the localization of a single object in a scene with arbitrary background. We show how the global pose sea...

Previous work on 3D action recognition has focused on using hand-designed features, either from depth videos or 2D videos. In this work, we present an effective way to combine unsupervised feature learning with discriminative feature mining. Unsupervised feature learning allows us to extract spatio-temporal features from unlabeled video data. With this, we can avoid the cumbersome process of de...

The structure of the human brain reflects multifarious random influences terrestrial and phylogenetic history, yet higher mental functions correlated with this unique cerebral neurophysiology are generally assumed to embody universals common intelligences independent biological substrate.

During face-to-face interpersonal interaction people have a tendency to mimic each other, that is, they change their own behaviors to adjust to the behavior expressed by a partner. In this paper we describe how behavioral information expressed between two interlocutors can be used to detect and identify mimicry and improve recognition of interrelationship and affect between them in a conversati...

Choosing appropriate classification algorithms for a given data set is very important and useful in practice but also is full of challenges. In this paper, a method of recommending classification algorithms is proposed. Firstly the feature vectors of data sets are extracted using a novel method and the performance of classification algorithms on the data sets is evaluated. Then the feature vect...

3D scene analysis by automatically assigning 3D points a semantic label has become an issue of major interest in recent years. Whereas the tasks of feature extraction and classification have been in the focus of research, the idea of using only relevant and more distinctive features extracted from optimal 3D neighborhoods has only rarely been addressed in 3D lidar data processing. In this paper...