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DRT: Detection Refinement for Multiple Object Tracking
2021
British Machine Vision Conference
Preserved Fulltext
This paper proposes Detection Refinement for Tracking (DRT) to address these two issues for people tracking. ...
Deep learning methods have led to remarkable progress in multiple object tracking (MOT). ...
WANG, ET AL.: DRT: DETECTION REFINEMENT FOR MULTIPLE OBJECT TRACKING ...
dblp:conf/bmvc/WangFPBC21
fatcat:i4dmjznajbguhi7pmnx6zmupl4
A detailed analysis of anatomical plausibility of crossed and uncrossed streamline rendition of the dentato-rubro-thalamic tract (DRT(T)) in a commercial stereotactic planning system
2021
Acta Neurochirurgica
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For tracking BrainLab Elements (BrainLab, Munich, Germany), two tensor deterministic tracking (FT2), MRtrix IFOD2 (https://www.mrtrix.org), and a global tracking (GT) approach were used to compare the ...
An evaluation of the anatomical validity of the display of the DRT with respect to modern stereotactic planning systems and across different tracking environments has not been performed. ...
The authors showed similar results for streamline display of the DRT and were equally unsuccessful for the detection of DRTx. ...
doi:10.1007/s00701-021-04890-4
pmid:34181083
pmcid:PMC8437929
fatcat:b5afmfb2sbfc5omuynprxtwwly
TransFiner: A Full-Scale Refinement Approach for Multiple Object Tracking
[article]
2022
arXiv
pre-print
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Multiple object tracking (MOT) is the task containing detection and association. Plenty of trackers have achieved competitive performance. ...
In this paper, we propose TransFiner, a transformer-based post-refinement approach for MOT. ...
Introduction Multiple object tracking (MOT) refers to linking identical detections across frames and primarily exists in the form of two mainstream paradigms, namely tracking-by-detection (TBD) and joint ...
arXiv:2207.12967v1
fatcat:tq3vczmvavhstkejx2mtvhanpm
Deep Learning for Visual Tracking: A Comprehensive Survey
[article]
2019
arXiv
pre-print
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visual tracking, network objective, network output, and the exploitation of correlation filter advantages. ...
It may serve as a gentle use guide for practitioners to weigh on when and under what conditions to choose which method(s). ...
Kamal Nasrollahi (Visual Analysis of People Lab (VAP), Aalborg University) for his beneficial comments. ...
arXiv:1912.00535v1
fatcat:v5ikqi2cpbblhgtkiu6z6l5anq
Iterative Multiple Bounding-Box Refinements for Visual Tracking
2022
Journal of Imaging
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Single-object visual tracking aims at locating a target in each video frame by predicting the bounding box of the object. ...
Empirical results demonstrate that the proposed approach improves the iterative single refinement in terms of accuracy and precision of the tracking results. ...
In [13] , the method for object detection in [12] is adapted to perform visual tracking. ...
doi:10.3390/jimaging8030061
pmid:35324616
pmcid:PMC8955588
fatcat:gbvzqzlytrbcthscfhki3ojjqu
Correlation Tracking via Joint Discrimination and Reliability Learning
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. ...
Since most of CNN models are pre-trained with respect to the task of object classification or detection, they tend to retain the features useful for distinguishing different categories of objects, and ...
Since our method jointly considers both discrimination and reliability for tracking, we denote it as DRT for clarity. ...
doi:10.1109/cvpr.2018.00058
dblp:conf/cvpr/Sun0L018
fatcat:itu5rjundvcdvci2ypoy4b4twm
Correlation Tracking via Joint Discrimination and Reliability Learning
[article]
2018
arXiv
pre-print
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For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. ...
Since our method jointly considers both discrimination and reliability for tracking, we denote it as DRT for clarity. ...
Since most of CNN models are pre-trained with respect to the task of ob-ject classification or detection, they tend to retain the features useful for distinguishing different categories of objects, and ...
arXiv:1804.08965v1
fatcat:yplg4qk3lzb5rpbih2jv6msbem
Real-time prediction of short-timescale fluctuations in cognitive workload
2021
Cognitive Research
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We used cross-validation to assess whether measures related to task performance immediately preceding the DRT could predict detection performance as a proxy for cognitive workload. ...
We showed that the DRT provided a valid measure that can detect differences in workload due to changes in the number of UAVs. ...
Similar to a multiple-object tracking task, UAVs were not labeled and moved at a pace that made it easy to track a single UAV, with difficulties arising only when simultaneously following multiple UAVs ...
doi:10.1186/s41235-021-00289-y
pmid:33835271
fatcat:ns6a7atkxvdmdfcel6mlrhmbui
Design Boundary Objects - Development Guidelines for Financial Data Warehouse Projects
2010
European Conference on Information Systems
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To address complexities in the context of design processes that involve multiple heterogeneous social worlds, Bergman et al. (2007) introduced the concept of design boundary objects with four essential ...
As a result of our analysis we propose a set of guidelines for the better development of design boundary objects in complex settings such as financial data warehousing projects. ...
to track their current status. ...
dblp:conf/ecis/VranesicRR10
fatcat:eygchbso7zdzbg25luhdgkowuy
Understanding dynamic scenes based on human sequence evaluation
2009
Image and Vision Computing
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For this purpose, a human behaviour model based on Situation Graph Trees (SGTs) is considered, which permits both bottom-up (hypothesis generation) and top-down (hypothesis refinement) analysis of dynamic ...
The resulting system prototype interprets different kinds of behaviour and reports textual descriptions in multiple languages. ...
Thanks to the anonymous referees for their comments which inspired us to enhance the initial version. ...
doi:10.1016/j.imavis.2008.02.004
fatcat:c3s5hkm7kja25ksdfqfhz4zb5q
Automated driving reduces perceived workload, but monitoring causes higher cognitive load than manual driving
2019
Transportation Research Part F: Traffic Psychology and Behaviour
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Acknowledgment We kindly thank Paul van Gent for providing us with the heart rate and GPS equipment, and his support in pre-processing the cardiovascular recordings. ...
Detection response task (DRT) The auditory DRT was performed as an objective measure of changes in cognitive load. ...
An auditory detection response task (DRT) was performed as an objective measure of the driver's cognitive workload. The DRT was implemented in Python on a Raspberry PI 3B running Raspbian Jessie. ...
doi:10.1016/j.trf.2018.11.006
fatcat:rgaabyq4zfg2bgyezyzlcldsve
Modelling and Validating a multiple-configuration railway signalling system using SDL
2003
Electronical Notes in Theoretical Computer Science
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This paper discusses some issues about the usage of SDL and related commercial SDL support tools for the validation of a railway signalling system: in particular, the issue of the multiple configurations ...
Becucci for carrying on the validation experiments, and General Electric Transportation Systems for kindly lending the case study. ...
The SCA system is composed by several Control and Acquisition Units, named UCAs, placed along the tracks, and by Detection Points placed aside the track, named PRAs. ...
doi:10.1016/s1571-0661(04)81026-0
fatcat:sodzey2v6bdwfofkq7gsqsjmpe
Siamese Keypoint Prediction Network for Visual Object Tracking
[article]
2020
arXiv
pre-print
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SiamKPN performs well against state-of-the-art trackers for visual object tracking on four benchmark datasets including OTB-100, VOT2018, LaSOT and GOT-10k, while running at real-time speed. ...
Visual object tracking aims to estimate the location of an arbitrary target in a video sequence given its initial bounding box. ...
Like other computer vision tasks such as image classification, object detection and semantic segmentation, object tracking is very challenging due to appearance variations caused by deformation, viewpoint ...
arXiv:2006.04078v1
fatcat:szr7f2irwrbh7ccg7xkgdhqne4
The Sixth Visual Object Tracking VOT2018 Challenge Results
[chapter]
2019
Lecture Notes in Computer Science
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The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. ...
The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis and a "real-time" experiment simulating a situation where a tracker processes images as if provided ...
In long-term tracking, few trackers can re-detect the object after tracking failures. ...
doi:10.1007/978-3-030-11009-3_1
fatcat:wbfi2kp3rze33cl2o56eauhooq
An efficient and parallel level set reinitialization method – Application to micromechanics and microstructural evolutions
2015
Applied Mathematical Modelling
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Different test cases illustrate the potential of the method for typical metallurgical and micromechanical problems with isotropic and anisotropic meshes. ...
The paper introduces a new parallel and efficient algorithm for the reinitialization of level set functions on unstructured Finite Element (FE) meshes in two and three dimensions. ...
The interface of this parasite phase is then automatically detected and captured by the remesher which adapts the mesh around it. ...
doi:10.1016/j.apm.2015.03.014
fatcat:pxrsb2hytbganitzche55vux2y
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