We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
In this paper, we propose an adaptive 3D-DCT compression technique, which dynamically determines an optimal size of the video cube based on the motion analysis. The technique cons...
Borko Furht, Ken Gustafson, Hesong Huang, Oge Marq...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
Dimensionality reduction techniques seek to represent a set of images as a set of points in a low dimensional space. Here we explore a video representation that considers a video ...
In this paper we present a system for classifying various human actions in compressed domain video framework. We introduce the notion of quantifying the motion involved, through w...