Multiple object tracking: A literature review
Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …
and commercial potential. Although different approaches have been proposed to tackle this …
Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
Tracking-learning-detection
This paper investigates long-term tracking of unknown objects in a video stream. The object
is defined by its location and extent in a single frame. In every frame that follows, the task is …
is defined by its location and extent in a single frame. In every frame that follows, the task is …
Robust object tracking with online multiple instance learning
In this paper, we address the problem of tracking an object in a video given its location in the
first frame and no other information. Recently, a class of tracking techniques called “tracking …
first frame and no other information. Recently, a class of tracking techniques called “tracking …
A survey of advances in vision-based human motion capture and analysis
This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …
You'll never walk alone: Modeling social behavior for multi-target tracking
S Pellegrini, A Ess, K Schindler… - 2009 IEEE 12th …, 2009 - ieeexplore.ieee.org
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 …
past trajectory. In crowded scenarios a strong dynamic model is particularly important …
Tracking the untrackable: Learning to track multiple cues with long-term dependencies
The majority of existing solutions to the Multi-Target Tracking (MTT) problem do not combine
cues over a long period of time in a coherent fashion. In this paper, we present an online …
cues over a long period of time in a coherent fashion. In this paper, we present an online …
Learning to track: Online multi-object tracking by decision making
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 …
analysis scenarios, such as robot navigation and autonomous driving. In tracking-by …
Multiple object tracking using k-shortest paths optimization
Multi-object tracking can be achieved by detecting objects in individual frames and then
linking detections across frames. Such an approach can be made very robust to the …
linking detections across frames. Such an approach can be made very robust to the …