Results 61 to 70 of about 711,042 (336)
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
DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM [PDF]
IEEE Robotics and Automation Letters, 2020 The assumption of scene rigidity is common in visual SLAM algorithms. However, it limits their applicability in populated real-world environments. Furthermore, most scenarios including autonomous driving, multi-robot collaboration and augmented/virtual ...
Berta Bescós +3 more
semanticscholar +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
openaire +2 more sources
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
CollabMOT Stereo Camera Collaborative Multi Object Tracking
IEEE AccessThe recent advances in deep learning techniques enable 2D Multi-object tracking (MOT) to achieve remarkable performance over traditional methods. However, most 2D MOT algorithms primarily utilize only single-camera view.
Phong Phu Ninh, Hyungwon Kim
doaj +1 more source
Single and multiple object tracking using a multi-feature joint sparse representation [PDF]
, 2015 In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is
Hu, W. +3 more
core +1 more source
Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors [PDF]
IEEE transactions on intelligent transportation systems (Print)Autonomous driving holds great promise in addressing traffic safety concerns by leveraging artificial intelligence and sensor technology. Multi-Object Tracking plays a critical role in ensuring safer and more efficient navigation through complex traffic ...
Lei Cheng, Arindam Sengupta, Siyang Cao
semanticscholar +1 more source
Correlation‐guided multi‐object tracking with correlation feature transfer
IET Computer Vision, 2019 Here, the authors propose a correlation‐guided Monte Carlo Markov chain (MCMC) solver to promote the efficiency for tracking multiple objects under recursive Bayesian filtering framework.
Jiatong Li, Yanjie Zhao, Zhiguo Jiang
doaj +1 more source