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 …
Features for multi-target multi-camera tracking and re-identification
Abstract Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …
taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images …
Performance measures and a data set for multi-target, multi-camera tracking
To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a
new pair of precision-recall measures of performance that treats errors of all types uniformly …
new pair of precision-recall measures of performance that treats errors of all types uniformly …
Deep affinity network for multiple object tracking
Multiple Object Tracking (MOT) plays an important role in solving many fundamental
problems in video analysis and computer vision. Most MOT methods employ two steps …
problems in video analysis and computer vision. Most MOT methods employ two steps …
Online multi-object tracking using CNN-based single object tracker with spatial-temporal attention mechanism
In this paper, we propose a CNN-based framework for online MOT. This framework utilizes
the merits of single object trackers in adapting appearance models and searching for target …
the merits of single object trackers in adapting appearance models and searching for target …
UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking
Effective multi-object tracking (MOT) methods have been developed in recent years for a
wide range of applications including visual surveillance and behavior understanding …
wide range of applications including visual surveillance and behavior understanding …
Real-time part-based visual tracking via adaptive correlation filters
Robust object tracking is a challenging task in computer vision. To better solve the partial
occlusion issue, part-based methods are widely used in visual object trackers. However, due …
occlusion issue, part-based methods are widely used in visual object trackers. However, due …
Posetrack: Joint multi-person pose estimation and tracking
In this work, we introduce the challenging problem of joint multi-person pose estimation and
tracking of an unknown number of persons in unconstrained videos. Existing methods for …
tracking of an unknown number of persons in unconstrained videos. Existing methods for …
The unmanned aerial vehicle benchmark: Object detection, tracking and baseline
With the increasing popularity of Unmanned Aerial Vehicles (UAVs) in computer vision-
related applications, intelligent UAV video analysis has recently attracted the attention of an …
related applications, intelligent UAV video analysis has recently attracted the attention of an …
Deft: Detection embeddings for tracking
Most modern multiple object tracking (MOT) systems follow the tracking-by-detection
paradigm, consisting of a detector followed by a method for associating detections into …
paradigm, consisting of a detector followed by a method for associating detections into …