Multiple hypothesis tracking addresses difficult multiple target tracking problems by making
association decisions using multiple scans or frames of data. This paper reviews forty years …

Multiple pedestrian tracking (MPT) has gained significant attention due to its huge potential
in a commercial application. It aims to predict multiple pedestrian trajectories and maintain …

Advanced driver assistance systems (ADASs), and particularly pedestrian protection
systems (PPSs), have become an active research area aimed at improving traffic safety. The …

We present a coherent, discriminative framework for simultaneously tracking multiple people
and estimating their collective activities. Instead of treating the two problems separately, our …

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 …

In this paper, we show that tracking multiple people whose paths may intersect can be
formulated as a multi-commodity network flow problem. Our proposed framework is …

This paper presents a principled framework for analyzing collective activities at different
levels of semantic granularity from videos. Our framework is capable of jointly tracking …

In this paper, a Random Field Topic (RFT) model is proposed for semantic region analysis
from motions of objects in crowded scenes. Different from existing approaches of learning …

Many state-of-the-art approaches to multi-object tracking rely on detecting them in each
frame independently, grouping detections into short but reliable trajectory segments, and …

The main problem in multiple object tracking is data association, which has a natural
representation as a graph. This paper reviews two different graph approaches for solving the …