This paper addresses the problem of human pose estimation, given images taken from multiple dynamic but calibrated cameras. We consider solving this task using a part-based model and focus on the part appearance component of such a model. We use a random forest classifier to capture the variation in appearance of body parts in 2D images. The result of these 2D part detectors are then aggregated...

Background

The aim of this study is to explore how we could use computational technology to help determination of the chronology of music manuscripts. Applying a battery of techniques to Bach’s manuscripts reveals the limitation in current image processing techniques, thereby clarifying future tasks. Analysis of C-clefs, the chosen musical symbol for this study, extracted from Bach’s manuscripts dating fr...

We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while...

In a recent paper Broutin and Devroye (2005) have studied the height of a class of edge-weighted random trees. This is a class of trees growing in continuous time which includes many well known trees as examples. In this paper we derive a limit theorem for the internal path length for this class of trees. The application of this limit theorem to concrete examples depends upon the possibility to...

As a testament to their success, the theory of random forests has long been outpaced by their application in practice. In this paper, we take a step towards narrowing this gap by providing a consistency result for online random forests.

We study depth properties of a general class of random recursive trees where each node i attaches to the random node biXic and X0, . . . , Xn is a sequence of i.i.d. random variables taking values in [0, 1). We call such trees scaled attachment random recursive trees (sarrt). We prove that the height Hn of a sarrt is asymptotically given by Hn ∼ αmax logn where αmax is a constant depending only...