A natural way to characterize the cluster structure of a dataset is by finding regions
containing a high density of data. This can be done in a nonparametric way with a kernel …

We present an efficient and scalable technique for spatiotemporal segmentation of long
video sequences using a hierarchical graph-based algorithm. We begin by over-segmenting …

Feature space analysis is the main module in many computer vision tasks. The most popular
technique, k-means clustering, however, has two inherent limitations: the clusters are …

Real-world actions occur often in crowded, dynamic environments. This poses a difficult
challenge for current approaches to video event detection because it is difficult to segment …

We present an interactive system for efficiently extracting foreground objects from a video.
We extend previous min-cut based image segmentation techniques to the domain of video …

Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …

Video provides not only rich visual cues such as motion and appearance, but also much less
explored long-range temporal interactions among objects. We aim to capture such …

Supervoxel segmentation has strong potential to be incorporated into early video analysis
as superpixel segmentation has in image analysis. However, there are many plausible …

In this paper, we present a new framework of video object segmentation, in which we
formulate the task of extracting prominent objects from a scene as the problem of …

We describe a system for transforming an input video into a highly abstracted, spatio-
temporally coherent cartoon animation with a range of styles. To achieve this, we treat video …