This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking-
by-detection framework. The success of MHT largely depends on the ability to maintain a …

Abstract Online Multi-Object Tracking (MOT) has wide applications in time-critical video
analysis scenarios, such as robot navigation and autonomous driving. In tracking-by …

Abstract We propose Quadruplet Convolutional Neural Networks (Quad-CNN) for multi-
object tracking, which learn to associate object detections across frames using quadruplet …

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with
each incoming frame and the information provided up to the moment. It still remains a …

Online multi-object tracking aims at producing complete tracks of multiple objects using the
information accumulated up to the present moment. It still remains a difficult problem in …

Data association problems are an important component of many computer vision
applications, with multi-object tracking being one of the most prominent examples. A typical …

In this paper, we address the problem of automatically detecting and tracking a variable
number of persons in complex scenes using a monocular, potentially moving, uncalibrated …

We propose a novel approach for multi-person tracking-by-detection in a particle filtering
framework. In addition to final high-confidence detections, our algorithm uses the continuous …

Online multi-object tracking (MOT) is extremely important for high-level spatial reasoning
and path planning for autonomous and highly-automated vehicles. In this paper, we present …

Online multi-object tracking with a single moving camera is a challenging problem as the
assumptions of 2D conventional motion models (eg, first or second order models) in the …