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A Honey Bee In-and-Out Counting Method Based on Multiple Object Tracking Algorithm. [PDF]
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ACM Computing Surveys, 2006
The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, nonrigid object ...
Yilmaz, Alper +2 more
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The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, nonrigid object ...
Yilmaz, Alper +2 more
openaire +4 more sources
Improving Multiple Object Tracking with Single Object Tracking
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021Despite considerable similarities between multiple object tracking (MOT) and single object tracking (SOT) tasks, modern MOT methods have not benefited from the development of SOT ones to achieve satisfactory performance. The major reason for this situation is that it is inappropriate and inefficient to apply multiple SOT models directly to the MOT task,
Linyu Zheng +5 more
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2016 23rd International Conference on Pattern Recognition (ICPR), 2016
In this paper, we address the problem of visual tracking in videos without using a pre-learned model of the object. This type of model-free tracking is a hard problem because of limited information about the object, abrupt object motion, and shape deformation.
Ivan Bogun, Eraldo Ribeiro
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In this paper, we address the problem of visual tracking in videos without using a pre-learned model of the object. This type of model-free tracking is a hard problem because of limited information about the object, abrupt object motion, and shape deformation.
Ivan Bogun, Eraldo Ribeiro
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Sparsely-Supervised Object Tracking
IEEE Transactions on Image ProcessingRecent years have witnessed the incredible performance boost of data-driven deep visual object trackers. Despite the success, these trackers require millions of sequential manual labels on videos for supervised training, implying the heavy burden of human annotating.
Jilai Zheng +3 more
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2014
The moving objects tracking system aims to monitor the locations of a set of objects which are traveling in a certain space, such as animals in fields and cars in road networks. It is a popular problem due to the importance in various application scenarios.
Xiaofeng Meng, Zhiming Ding, Jiajie Xu
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The moving objects tracking system aims to monitor the locations of a set of objects which are traveling in a certain space, such as animals in fields and cars in road networks. It is a popular problem due to the importance in various application scenarios.
Xiaofeng Meng, Zhiming Ding, Jiajie Xu
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2012 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS) Proceedings, 2012
This paper presents an improved kernel-based target tracking that uses new and effective features able to describe the target appearance. The key idea consists of adopting features that are related to the visual perception of the target in place of its color histogram. The change of the feature space is twofold advantageous.
BRUNI, VITTORIA +2 more
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This paper presents an improved kernel-based target tracking that uses new and effective features able to describe the target appearance. The key idea consists of adopting features that are related to the visual perception of the target in place of its color histogram. The change of the feature space is twofold advantageous.
BRUNI, VITTORIA +2 more
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2018
Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target.
Shengrong Gong +5 more
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Moving object tracking is to find out the candidate object region which is the most similar area in the image sequence through the effective expression of the object, that is to locate the target in the sequence image so as to obtain the complete motion trajectory of the moving target.
Shengrong Gong +5 more
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2020
The classic Bayes-Markov (BM), probabilistic data association (PDA), and integrated PDA (IPDA) filters are derived using the analytic combinatorics (AC) method. The probability generating functional (GFL) of the BM filter is an integral, obtained as the limit of a Riemann sum of a discrete problem discussed in Chap. 1.
Roy Streit +2 more
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The classic Bayes-Markov (BM), probabilistic data association (PDA), and integrated PDA (IPDA) filters are derived using the analytic combinatorics (AC) method. The probability generating functional (GFL) of the BM filter is an integral, obtained as the limit of a Riemann sum of a discrete problem discussed in Chap. 1.
Roy Streit +2 more
openaire +1 more source
A map of object space in primate inferotemporal cortex
Nature, 2020Pinglei Bao, Liang She, Doris Y Tsao
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