Object class detection, also known as category-level object detection, has become one of
the most focused areas in computer vision in the new century. This article attempts to …

Cascades are a popular framework to speed up object detection systems. Here we focus on
the first layers of a category independent object detection cascade in which we sample a …

In highway traffic monitoring systems, vehicle detection is one of the most important tasks. To
automatically detect vehicles in general CCTV environments, we should effectively handle …

Pattern retrieval is a fundamental challenge in machine learning but is often subject to the
problem of gathering enough labeled examples of the target pattern, and also to the …

We describe an efficient approach to visual object detection that uses short cascades of
asymmetric 'one class' classifiers to quickly reject negatives (windows not centered on an …

This paper focuses on the problem of detecting a number of different class objects in
images. We present a novel part-based model for object detection with cascaded classifiers …

Divergence measures provide a means to measure the pairwise dissimilarity between
“objects”, eg, vectors and probability density functions (pdfs). Kullback-Leibler (KL) …

In this paper, an effective algorithm is developed to learn more discriminative multi-class
classifiers for achieving more accurate hand detection. At each round of boosting, a set of …

In this paper we present a novel template-based approach for fast object detection. In
particular we investigate the use of Dominant Orientation Templates (DOT), a binary …

The aim of this dissertation is the automatic detection of vehicles. Utilized features are
regions and gradients. The final detection is carried out with a supervised cascaded …