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Random Forests (RFs) are frequently used in many computer vision and machine learning applications. Their popularity is mainly driven by their high computational efficiency during both training and evaluation while still achieving state-of-the-art results. However, in most applications RFs are used off-line. This limits their usability for many practical(More)
Online learning has shown to be successful in tracking of previously unknown objects. However, most approaches are limited to a bounding-box representation with fixed aspect ratio. Thus, they provide a less accurate fore-ground/background separation and cannot handle highly non-rigid and articulated objects. This, in turn, increases the amount of noise(More)
The paper presents contributions to the design of the Flock of Trackers (FoT). The FoT track-ers estimate the pose of the tracked object by robustly combining displacement estimates from local track-ers that cover the object. The first contribution, called the Cell FoT, allows local trackers to drift to points good to track. The Cell FoT was compared with(More)
Online boosting is one of the most successful on-line learning algorithms in computer vision. While many challenging online learning problems are inherently multi-class, online boosting and its variants are only able to solve binary tasks. In this paper, we present Online Multi-Class LPBoost (OMCLP) which is directly applicable to multi-class problems. From(More)
In this paper a method for the automated identification of tree species from images of leaves, bark and needles is presented. The automated identification of leaves uses local features to avoid segmen-tation. For the automated identification of images of the bark this method is compared to a combination of GLCM and wavelet features. For classification a(More)
With the increasing availability of annotated multimedia data on the Internet, techniques are in demand that allow for a principled joint processing of different types of data. Multiview learning and multiview clustering attempt to identify latent components in different features spaces in a simultaneous manner. The resulting basis vectors or centroids(More)
An American family of English origin with an unusually early onset and long-duration form of Creutzfeldt-Jakob disease (CJD) had a heterozygous insert mutation in the region of repeating octapeptide coding sequences between codons 51 and 91 of the PRNP gene on chromosome 20. Affected members were 23 to 35 years old at the onset of illnesses that lasted from(More)
Current state-of-the-art object classification systems are trained using large amounts of hand-labeled images. In this paper, we present an approach that shows how to use unlabeled video sequences, comprising weakly-related object categories towards the target class, to learn better classifiers for tracking and detection. The underlying idea is to exploit(More)
The relationship between neuritic plaque formation in Alzheimer's disease and cholinergic innervation of brain regions is unclear. Many neuritic plaques are found in the amygdala, which also receives dense cholinergic innervation from the ventral forebrain, predominantly to the basolateral complex. To determine whether the regional distribution of neuritic(More)
—Randomized learning methods (i.e., Forests or Ferns) have shown excellent capabilities for various computer vision applications. However, it was shown that the tree structure in Forests can be replaced by even simpler structures, e.g., Random Naive Bayes classifiers, yielding similar performance. The goal of this paper is to benefit from these findings to(More)