Due to the resource limitation in the data stream environment, it has been reported that answering user queries according to the wavelet synopsis of a stream is an essential abili...
Fast indexing in time sequence databases for similarity searching has attracted a lot of research recently. Most of the proposals, however, typically centered around the Euclidean...
There has been much recent interest in adapting data mining algorithms to time series databases. Most of these algorithms need to compare time series. Typically some variation of ...
The distance transform (DT) and the medial axis transform (MAT) are two image computation tools used to extract the information about the shape and the position of the foreground ...
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...
Although k-means clustering is often applied to time series clustering, the underlying Euclidean distance measure is very restrictive in comparison to the human perception of time ...
Let P be a set of n points in Rd. The radius of a k-dimensional flat F with respect to P, denoted by RD(F, P), is defined to be maxp∈P dist(F, p), where dist(F, p) denotes the...
Data-driven animation has become the industry standard for computer games and many animated movies and special effects. In particular, motion capture data recorded from live actor...
Eamonn J. Keogh, Themis Palpanas, Victor B. Zordan...
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
Claudio Varini, Andreas Degenhard, Tim W. Nattkemp...
An important consideration in similarity-based retrieval of moving object trajectories is the definition of a distance function. The existing distance functions are usually sensi...