We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Given two sets A and B of m non-intersecting line segments in the plane, we show how to compute in O(m log m) time a data structure that uses O(m) space and allows to answer the fo...
Otfried Cheong, Hazel Everett, Hyo-Sil Kim, Sylvai...
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we con...
In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...