In this work, we systematically study the problem of event recognition in unconstrained news video sequences. We adopt the discriminative kernel-based method for which video clip s...
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
We propose a new method for warping highresolution images to efficiently track objects on the ground plane in real time. Recently, the emergence of high resolution video cameras (...
Tae Eun Choe, Krishnan Ramnath, Mun Wai Lee, Niels...
The aim of this work is to devise an effective method for static summarization of home video sequences. Based on the premise that the user watching a summary is interested in peop...
We propose an innovative, general purpose, approach to the selection and hierarchical representation of key frames of a video sequence for video summarization. In the first stage ...