Abstract The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-
term single-object visual trackers that do not apply pre-learned models of object …

A general non-parametric technique is proposed for the analysis of a complex multimodal
feature space and to delineate arbitrarily shaped clusters in it. The basic computational …

We show that the complexity of the recently introduced medoid-shift algorithm in clustering N
points is O (N 2), with a small constant, if the underlying distance is Euclidean. This makes …

In this paper, we address the problem of detecting pedestrians in crowded real-world scenes
with severe overlaps. Our basic premise is that this problem is too difficult for any type of …

The mean-shift algorithm is an efficient technique for tracking 2D blobs through an image.
Although the scale of the mean-shift kernel is a crucial parameter, there is presently no clean …

This paper presents a novel method for detecting and localizing objects of a visual category
in cluttered real-world scenes. Our approach considers object categorization and figure …

Detection and tracking of humans in video streams is important for many applications. We
present an approach to automatically detect and track multiple, possibly partially occluded …

Accurate identification of cell subsets in complex populations is key to discovering novelty in
multidimensional single-cell experiments. We present X-shift (http://web. stanford. edu …

The most prevalent cancer amongst women is woman breast cancer. Ultrasound imaging is
a widely employed method for identifying and diagnosing breast abnormalities. Computer …

We propose a filtering feature selection framework that considers subsets of features as
paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) …