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Multi‐object tracking using dominant sets
IET Computer Vision, 2016 Multi‐object tracking is an interesting but challenging task in the field of computer vision. Most previous works based on data association techniques merely take into account the relationship between detection responses in a locally limited temporal ...
Yonatan T. Tesfaye +3 more
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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
Efficient Online Tracking-by-Detection With Kalman Filter
IEEE Access, 2021 Visual tracking of multiple objects in videos has a promisingly broad application in manufacturing, construction, traffic, logistics, etc., especially in large-scale applications where it is not feasible to attach markers to many objects for traditional,
Siyuan Chen, Chenhui Shao
doaj +1 more source
Towards Frame Rate Agnostic Multi-object Tracking
International Journal of Computer Vision, 2023 Multi-Object Tracking (MOT) is one of the most fundamental computer vision tasks that contributes to various video analysis applications. Despite the recent promising progress, current MOT research is still limited to a fixed sampling frame rate of the input stream. In fact, we empirically found that the accuracy of all recent state-of-the-art trackers
Weitao Feng +4 more
openaire +2 more sources
Survey on Strategies for Solving Target Overlap Issues in Multi-Object Tracking [PDF]
ITM Web of ConferencesWith the development of artificial intelligence and related fields, technologies for image recognition and tracking objects have been continuously innovating. Starting from the initial single-object tracking, through numerous research improvements, multi-
Wang Sizhe
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Multi-Object Tracking with Siamese Track-RCNN
, 2020 Multi-object tracking systems often consist of a combination of a detector, a short term linker, a re-identification feature extractor and a solver that takes the output from these separate components and makes a final prediction. Differently, this work aims to unify all these in a single tracking system.
Shuai, Bing +3 more
openaire +2 more sources
Multiple Pedestrians and Vehicles Tracking in Aerial Imagery Using a Convolutional Neural Network
Remote Sensing, 2021 In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-resolution aerial imagery by intensive evaluation of a number of traditional and Deep Learning based Single- and Multi-Object Tracking methods. We also describe
Seyed Majid Azimi +3 more
doaj +1 more source
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers [PDF]
, 2019 Online Multi-Object Tracking (MOT) from videos is a challenging computer vision task which has been extensively studied for decades. Most of the existing MOT algorithms are based on the Tracking-by-Detection (TBD) paradigm combined with popular machine ...
Barber, David +4 more
core +2 more sources
Measurement-Wise Occlusion in Multi-Object Tracking [PDF]
2018 21st International Conference on Information Fusion (FUSION), 2018 Handling object interaction is a fundamental challenge in practical multi-object tracking, even for simple interactive effects such as one object temporarily occluding another. We formalize the problem of occlusion in tracking with two different abstractions.
Motro, Michael, Ghosh, Joydeep
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Visual Multiple-object Tracking Algorithm Based on Motion Consistency
Kongzhi Yu Xinxi Jishu, 2023 The visual multiple-object tracking module is a key component of an active onboard obstacle detection system. However, the most of currently used visual multiple-object tracking algorithms rely on offline calculation for object detection, without ...
YANG Hailang +5 more
doaj +3 more sources