Distance sampling detection functions: 2D or not 2D?

2D or not 2D? That is the question.

Recent work in automatic face recognition indicates that the major problem in modeling face processing is to find a meaningful representation for the faces. The difficulty arises from the often noted fact that human faces constitute a set of highly similar objects. Hence, a first constraint imposed upon a facial representation is that it must capture the subtle variations in features and config...

Mixture Models for Distance Sampling Detection Functions

We present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features of the widely-used "key function plus series adjustment" (K+A) formulation: they are flexible, produce plausible shapes with a small number of parameters, allow...

Sampling in cylindrical 2D PET

In this paper, we study 2D cylindrical Positron Emission Tomography (2D PET) sampling. We show that rectangular sampling schemes are more efficient than usual square schemes. 1. PET and sampling 1.1 PET The aim of Positron Emission Tomography (PET) is to map the internal nuclear activity of a patient from exterior measurement. Usually, the patient received some nuclear substance by inhalation o...

Distance Between Ellipses in 2D

2D or Not 2D: Bridging the Gap Between Tracking and Structure from Motion

In this paper, we address the problem of tracking an unknown object in 3D space. Online 2D tracking often fails for strong outof-plane rotation which results in considerable changes in appearance beyond those that can be represented by online update strategies. However, by modelling and learning the 3D structure of the object explicitly, such effects are mitigated. To address this, a novel appr...