This paper presents a framework for data modeling ntic abstraction of image/video data. The framework is based on spatio-temporalinformation associated with salient objects in an ...
Young Francis Day, Serhan Dagtas, Mitsutoshi Iino,...
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
In this paper, we present an unsupervised method for mining activities in videos. From unlabeled video sequences of a scene, our method can automatically recover what are the recu...
Ré, mi Emonet, Jagannadan Varadarajan, Jean-Marc ...
Time series data poses a significant variation to the traditional segmentation techniques of data mining because the observation is derived from multiple instances of the same und...
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...