Learn More
This paper presents new methods for automatic classification and retrieval of motion capture data facilitating the identification of logically related motions scattered in some database. As the main ingredient, we introduce the concept of motion templates (MTs), by which the essence of an entire class of logically related motions can be captured in an(More)
Preface In the past two decades, motion capture (mocap) systems have been developed that allow to track and record human motions at high spatial and temporal resolutions. The resulting motion capture data is used to analyze human motions in fields such as sports sciences and biometrics (person identification), and to synthesize realistic motion sequences in(More)
In this paper, we describe an efficient method for audio matching which performs effectively for a wide range of classical music. The basic goal of audio matching can be described as follows: consider an audio database containing several CD recordings for one and the same piece of music interpreted by various musicians. Then, given a short query audio clip(More)
Locating boundaries between coherent and/or repetitive segments of a time series is a challenging problem pervading many scientific domains. In this paper we propose an unsupervised method for boundary detection, combining three basic principles: novelty, homogene-ity, and repetition. In particular, the method uses what we call structure features, a(More)
The reuse of human motion capture data to create new, realistic motions by applying morphing and blending techniques has become an important issue in computer animation. This requires the identification and extraction of logically related motions scattered within some data set. Such content-based retrieval of motion capture data, which is the topic of this(More)
In recent years, depth cameras have become a widely available sensor type that captures depth images at real-time frame rates. Even though recent approaches have shown that 3D pose estimation from monocular 2.5D depth images has become feasible, there are still challenging problems due to strong noise in the depth data and self-occlusions in the motions(More)
Techniques based on non-negative matrix factorization (NMF) can be used to efficiently decompose a magnitude spectrogram into a set of template (column) vectors and activation (row) vectors. To better control this decomposition, NMF has been extended using prior knowledge and parametric models. In this paper, we present such an extended approach that uses(More)
Music signal processing may appear to be the junior relation of the large and mature field of speech signal processing, not least because many techniques and representations originally developed for speech have been applied to music, often with good results. However, music signals possess specific acoustic and structural characteristics that distinguish(More)