In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...
We present a correlation study of time-varying multivariate volumetric data sets. In most scientific disciplines, to test hypotheses and discover insights, scientists are interest...
This paper presents a novel framework for matching video sequences using the spatiotemporal segmentation of videos. Instead of using appearance features for region correspondence ...
In this paper, we address the issue of Euclidean path modeling in a single camera for activity monitoring in a multi-camera video surveillance system. The method consists of a pat...
—This paper describes a new method to explore and discover within a large data set. We apply techniques from preference elicitation to automatically identify data elements that a...