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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Object Tracking with Multiple Instance Learning and Gaussian Mixture Model [PDF]
, 2015 Recently, Multiple Instance Learning (MIL) technique has been introduced for object tracking\linebreak applications, which has shown its good performance to handle drifting problem. While some instances in positive bags not only contain objects, but also
Zhao, Xiangmo +4 more
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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
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Real-time multiple object tracking using virtual shells [PDF]
, 2012 This paper presents a new multiple object tracking framework where arbitrarily shaped complex objects having severe occlusions are successfully tracked in real-time using stationary cameras.
Erdoğan, Hakan +2 more
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A sparsity-driven approach to multi-camera tracking in visual sensor networks [PDF]
, 2013 In this paper, a sparsity-driven approach is presented for multi-camera tracking in visual sensor networks (VSNs). VSNs consist of image sensors, embedded processors and wireless transceivers which are powered by batteries. Since the energy and bandwidth
Çetin, Müjdat +3 more
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A Sequential Monte Carlo Approach for Extended Object Tracking in the Presence of Clutter [PDF]
, 2011 Extended objects are characterised with multiple measurements originated from ifferent locations of the object surface. This paper presents a novel Sequential Monte Carlo (SMC) approach for extended object tracking in the presence of clutter. The problem
Gning, Amadou +3 more
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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
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Segmentation-tracking feedback approach for high-performance video surveillance applications [PDF]
, 2010 Here, a novel and efficient feedback system for moving object segmentation and tracking is proposed. Through the use of non-parametric background-foreground modeling, moving objects are correctly detected in unfavorable situations such as dynamic ...
Narciso Garcia +7 more
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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
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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
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