We address the task of inferring the future actions of people from noisy visual input. We
denote this task activity forecasting. To achieve accurate activity forecasting, our approach …

Object tracking typically relies on a dynamic model to predict the object's location from its
past trajectory. In crowded scenarios a strong dynamic model is particularly important …

Object tracking and 3D reconstruction are often performed together, with tracking used as
input for reconstruction. However, the obtained reconstructions also provide useful …

We present a detection-based three-level hierarchical association approach to robustly track
multiple objects in crowded environments from a single camera. At the low level, reliable …

We present a novel approach for multi-object tracking which considers object detection and
spacetime trajectory estimation as a coupled optimization problem. Our approach is …

Multiple people tracking consists in detecting the subjects at each frame and matching these
detections to obtain full trajectories. In semi-crowded environments, pedestrians often …

Tracking object in low frame rate video or with abrupt motion poses two main difficulties
which most conventional tracking methods can hardly handle: 1) poor motion continuity and …

A fundamental requirement for effective automated analysis of object behavior and
interactions in video is that each object must be consistently identified over time. This is …

In this paper, we address the problem of multiperson tracking in busy pedestrian zones
using a stereo rig mounted on a mobile platform. The complexity of the problem calls for an …

This paper presents an online detection-based two-stage multi-object tracking method in
dense visual surveillances scenarios with a single camera. In the local stage, a particle filter …