Results 21 to 30 of about 627,313 (281)
Object Tracking Algorithm with Sparse Prototype Based on TLD [PDF]
Jisuanji gongcheng, 2017 Tracking-learning-detecting(TLD) object tracking algorithm can achieve a long time online tracking.But when the appearance changes of the object by the plane rotation and the object is occluded,the TLD tracking algorithm tracks drift in the process of ...
ZHOU Junna,CHEN Wei,WANG Ke,CAI Changzheng
doaj +1 more source
Effective Multi-Object Tracking via Global Object Models and Object Constraint Learning
Sensors, 2022 Effective multi-object tracking is still challenging due to the trade-off between tracking accuracy and speed. Because the recent multi-object tracking (MOT) methods leverage object appearance and motion models so as to associate detections between ...
Yong-Sang Yoo +2 more
doaj +1 more source
Semantic Enhanced Distantly Supervised Relation Extraction via Graph Attention Network
Information, 2020 Distantly Supervised relation extraction methods can automatically extract the relation between entity pairs, which are essential for the construction of a knowledge graph.
Xiaoye Ouyang, Shudong Chen, Rong Wang
doaj +1 more source
IEEE Access, 2021 Object tracking is an important basis for the autonomous navigation of unmanned surface vehicles. However, several problems still must be addressed for a wide applicating of object tracking in unmanned surface vehicles.
Qingze Yu, Bo Wang, Yumin Su
doaj +1 more source
Tracking of a Fixed-Shape Moving Object Based on the Gradient Descent Method
Sensors, 2022 Tracking moving objects is one of the most promising yet the most challenging research areas pertaining to computer vision, pattern recognition and image processing.
Haris Masood +6 more
doaj +1 more source
Object-Tracking Algorithm Combining Motion Direction and Time Series
Applied Sciences, 2023 Object tracking using deep learning is a crucial research direction within intelligent vision processing. One of the key challenges in object tracking is accurately predicting the object’s motion direction in consecutive frames while accounting for the ...
Jianjun Su, Chenmou Wu, Shuqun Yang
doaj +1 more source
Confidence-Guided Frame Skipping to Enhance Object Tracking Speed. [PDF]
Sensors (Basel)Object tracking is a challenging task in computer vision. While simple tracking methods offer fast speeds, they often fail to track targets. To address this issue, traditional methods typically rely on complex algorithms.
Lee YG.
europepmc +2 more sources
A New Object Tracking Framework for Interest Point Based Feature Extraction Algorithms
Elektronika ir Elektrotechnika, 2020 This paper presents a novel object tracking framework for interest point based feature extracting algorithms. The proposed framework uses the feature extracting algorithm without making any changes and it relies on outlier detection, object modelling ...
Zafer Guler, Ahmet Cinar, Erdal Ozbay
doaj +1 more source
Object-Centric Multiple Object Tracking
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 ICCV 2023 camera-ready ...
Zhao, Z. +15 more
openaire +3 more sources
Automatic Parameter Adaptation for Multi-object Tracking [PDF]
, 2013 Object tracking quality usually depends on video context (e.g. object occlusion level, object density). In order to decrease this dependency, this paper presents a learning approach to adapt the tracker parameters to the context variations. In an offline
Bremond, François +2 more
core +4 more sources