Driver and Pedestrian Mutual Awareness for Path Prediction in Intelligent Vehicles

This thesis addresses the sensor-based perception of driver and pedestrian to improve joint path prediction of ego-vehicle and pedestrian based on mutual awareness in the domain of intelligent vehicles.<br/><br/>According to the World Health Organization (WHO), more than half of global traffic deaths are among Vulnerable Road Users (VRUs), such...

IntrApose: Monocular Driver 6 DOF Head Pose Estimation Leveraging Camera Intrinsics

We present intrApose, a novel method for continuous 6 DOF head pose estimation from a single camera image without prior detection or landmark localization. We argue that using camera intrinsics alongside the intensity information is essential for accurate pose estimation. The proposed head pose estimation framework is crop-aware and scale...

Driver and Pedestrian Mutual Awareness for Path Prediction and Collision Risk Estimation

We present a novel method for vehicle-pedestrian path prediction that takes into account the awareness of the driver and the pedestrian towards each other. The method jointly models the paths of vehicle and pedestrian within a single Dynamic Bayesian Network (DBN). In this DBN, sub-graphs model the environment and entity-specific context cues...

Monotone trends in the distribution of climate extremes

The generalized Pareto distribution (GPD) is often used in the statistical analysis of climate extremes. For a sample of independent and identically distributed observations, the parameters of the GPD can be estimated by the maximum likelihood (ML) method. In this paper, we drop the assumption of identically distributed random variables. We...