Multiple human tracking (MHT) is a fundamental task in many computer vision applications.
Appearance‐based approaches, primarily formulated on RGB data, are constrained and …

We present a real-time RGB-D based multiperson detection and tracking system suitable for
mobile robots and head-worn cameras. Our approach combines RGB-D visual odometry …

Tracking in urban street scenes plays a central role in autonomous systems such as self-
driving cars. Most of the current vision-based tracking methods perform tracking in the image …

Object recognition is a critical next step for autonomous robots, but a solution to the problem
has remained elusive. Prior 3D-sensor-based work largely classifies individual point cloud …

This paper proposes a very fast and robust multi-people tracking algorithm suitable for
mobile platforms equipped with a RGB-D sensor. Our approach features a novel depth …

In this paper, we present a novel 2D–3D pedestrian tracker designed for applications in
autonomous vehicles. The system operates on a tracking by detection principle and can …

Assistive vision-based solutions for the driver extend the capabilities of human vision and
support safe travel. Unfortunately, their widespread usage is generally limited to expensive …

This paper addresses the problem of scene understanding for driver assistance systems. To
recognize the large number of objects that may be found on the road, several sensors and …

Classical tracking-by-detection approaches require a robust object detector that needs to be
executed in each frame. However the detector is typically the most computationally …

In this paper, we aim to take mobile multi-object tracking to the next level. Current
approaches work in a tracking-by-detection framework, which limits them to object …