Results 31 to 40 of about 627,313 (281)
Manifold Regularized Correlation Object Tracking [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2018 In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples.
Hongwei Hu +3 more
openaire +4 more sources
Parallel tracking and detection for long-term object tracking
International Journal of Advanced Robotic Systems, 2020 High tracking frame rates have been achieved based on traditional tracking methods which however would fail due to drifts of the object template or model, especially when the object disappears from the camera’s field of view.
Dan Xiong +5 more
doaj +1 more source
Multi-Object Tracking on SWIR Images for City Surveillance in an Edge-Computing Environment
Sensors, 2023 Although Short-Wave Infrared (SWIR) sensors have advantages in terms of robustness in bad weather and low-light conditions, the SWIR images have not been well studied for automated object detection and tracking systems.
Jihun Park +3 more
doaj +1 more source
Hierarchical fuzzy logic based approach for object tracking [PDF]
, 2013 In this paper a novel tracking approach based on fuzzy concepts is introduced. A methodology for both single and multiple object tracking is presented.
Couto, Pedro M. +3 more
core +1 more source
Remote Sensing, 2022 The task of multi-object tracking via deep learning methods for UAV videos has become an important research direction. However, with some current multiple object tracking methods, the relationship between object detection and tracking is not well handled,
Yeneng Lin +5 more
doaj +1 more source
Semantic and context features integration for robust object tracking
IET Image Processing, 2022 Siamese network‐based object tracking learns features of a target object marked in the first frame and that of the object in subsequent frames simultaneously and then measures similarity between two features to recognize and locate the object.
Jinzhen Yao +3 more
doaj +1 more source
Deep Feature Based Siamese Network for Visual Object Tracking
Energies, 2022 One of the most important and challenging research subjects in computer vision is visual object tracking. The information obtained from the first frame consists of limited and insufficient information to represent an object.
Su-Chang Lim, Jun-Ho Huh, Jong-Chan Kim
doaj +1 more source
Online Object Tracking with Proposal Selection [PDF]
, 2015 Tracking-by-detection approaches are some of the most successful object trackers in recent years. Their success is largely determined by the detector model they learn initially and then update over time.
Alahari, Karteek +2 more
core +6 more sources
On Pairwise Costs for Network Flow Multi-Object Tracking [PDF]
, 2015 Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and enable modeling of dependencies among tracks.
Chari, Visesh +3 more
core +1 more source
Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion [PDF]
, 2009 Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to the object dynamics.
Blanco Adán, Carlos Roberto del +3 more
core +2 more sources