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Multi-target Tracking in Crowded Scenes
2011In this paper, we propose a two-phase tracking algorithm for multi-target tracking in crowded scenes. The first phase extracts an overcomplete set of tracklets as potential fragments of true object tracks by considering the local temporal context of dense detection-scores. The second phase employs a Bayesian formulation to find the most probable set of
Jie Yu, Dirk Farin, Bernt Schiele
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Multi-target tracking using proximity sensors
2010 - MILCOM 2010 MILITARY COMMUNICATIONS CONFERENCE, 2010We consider the problem of tracking multiple moving targets in a continuous field using proximity sensors, which are binary sensors that can sense target presence by performing local energy detection subject to noise. Compared with more sophisticated sensors, proximity sensors have the advantage of having lower costs and lower energy consumption, but ...
Ting He +4 more
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Towards large scale multi-target tracking
SPIE Proceedings, 2014Multi-target tracking is intrinsically an NP-hard problem and the complexity of multi-target tracking solutions usually do not scale gracefully with problem size. Multi-target tracking for on-line applications involving a large number of targets is extremely challenging.
Ba-Ngu Vo +4 more
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Online Multi-Target Tracking with Tensor-Based High-Order Graph Matching
International Conference on Pattern Recognition, 2018In this paper we formulate multi-target tracking (MTT) as a high-order graph matching problem and propose a $\ell_{1}$-norm tensor power iteration solution.
Zongwei Zhou +3 more
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Problems in multi-target sonar tracking
1978 IEEE Conference on Decision and Control including the 17th Symposium on Adaptive Processes, 1978This paper discusses problems in the use of extended Kalman filtering and probabilistic decision making to carry out multi-sensor, multi-target, adaptive tracking for ocean surveillance. The key issues of data association, maneuver detection, and resource allocation are discussed, along with several open questions and research problems currently under ...
Thomas Fortmann, Sheldon Baron
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On Detection, Data Association and Segmentation for Multi-Target Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019In this work, we propose a tracker that differs from most existing multi-target trackers in two major ways. First, our tracker does not rely on a pre-trained object detector to get the initial object hypotheses.
Yicong Tian, Afshin Dehghan, M. Shah
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Robot detection with multi-target tracking
IEEE Conference on Cybernetics and Intelligent Systems, 2004., 2005We propose a vision-based method for detecting and tracking a mobile robot in dynamic, complex and unstructured environments, such as an office. When there are many moving objects (e.g. robot and persons) in the environment, and they interact with each other, it is not easy to estimate the correct correspondence between detected moving objects and ...
K. Tanaka, E. Kondo
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Multi-Target Tracking by Discrete-Continuous Energy Minimization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016The task of tracking multiple targets is often addressed with the so-called tracking-by-detection paradigm, where the first step is to obtain a set of target hypotheses for each frame independently. Tracking can then be regarded as solving two separate, but tightly coupled problems.
Anton Milan +2 more
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Research on multi-target tracking technology based on machine vision
Applied Nanoscience, 2022Dawei Yang
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Multi-target tracking of surveillance video with differential YOLO and DeepSort
International Conference on Digital Image Processing, 2019With the shortcomings of traditional algorithm in video surveillance on low accuracy, poor robustness and unable achieved real-time tracking for multi-targets, this paper presents a Multi-target tracking algorithm, DeepSort, on the base of deep neural ...
Xu Zhang +5 more
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