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Context-Aware and Occlusion Handling Mechanism for Online Visual Object Tracking

Khizer Mehmood, Abdul Jalil, Ahmad Ali, Baber Khan, Maria Murad, Wasim Ullah Khan, Yigang He
2020 Electronics  
In the present study, an adaptive Spatio-temporal context (STC)-based algorithm for online tracking is proposed by combining the context-aware formulation, Kalman filter, and adaptive model learning rate  ...  For the enhancement of seminal STC-based tracking performance, different contributions were made in the proposed study.  ...  The Principle of Spatio-Temporal Context and Correlation Filter Tracking STC Based Tracking In visual object tracking, the target is characterized by objects around the target present in the current  ... 
doi:10.3390/electronics10010043 fatcat:5g2ybycivbbdjdzvijjgfiis6a

Motion-Aware Correlation Filters for Online Visual Tracking

Yihong Zhang, Yijin Yang, Wuneng Zhou, Lifeng Shi, Demin Li
2018 Sensors  
In this paper, a novel Motion-Aware Correlation Filters (MACF) framework is proposed for online visual object tracking, where a motion-aware strategy based on joint instantaneous motion estimation Kalman  ...  filters is integrated into the Discriminative Correlation Filters (DCFs).  ...  (MDNet) [52] , Structure-Aware Network for visual tracking (SANet) [53] , Continuous Convolution Operators for visual Tracking (C-COT) [54] , Fully-Convolutional Siamese networks for object tracking  ... 
doi:10.3390/s18113937 fatcat:ubxlj77mlbacbdor4ktbgcqxyi

Correlation Filter-Based Visual Tracking for UAV with Online Multi-Feature Learning

Changhong Fu, Fuling Lin, Yiming Li, Guang Chen
2019 Remote Sensing  
The presented tracker uses novel features, i.e., intensity, color names, and saliency, to respectively represent both the tracking object and its background information in a background-aware correlation  ...  In the proposed response map fusion strategy, the peak-to-sidelobe ratio, which measures the peak strength of the response, is utilized to weight each response, thereby filtering the noise for each response  ...  Therefore, the background-aware correlation filter framework is adopted to conduct the object tracking applications for the UAV in this work.  ... 
doi:10.3390/rs11050549 fatcat:frymzcyhqfhxznozggovyyxjpa

Keyfilter-Aware Real-Time UAV Object Tracking [article]

Yiming Li, Changhong Fu, Ziyuan Huang, Yinqiang Zhang, Jia Pan
2020 arXiv   pre-print
Keyfilters generated by periodically selected keyframes learn the context intermittently and are used to restrain the learning of filters, so that 1) context awareness can be transmitted to all the filters  ...  Correlation filter-based tracking has been widely applied in unmanned aerial vehicle (UAV) with high efficiency. However, it has two imperfections, i.e., boundary effect and filter corruption.  ...  REVIEW OF BACKGROUND-AWARE CORRELATION FILTER The objective function of background-aware correlation filters (BACF) [12] is as follows: E(w) = 1 2 y − D d=1 Bx d 0 w d 2 2 + λ 2 D d=1 w d 2 2 , (1) where  ... 
arXiv:2003.05218v1 fatcat:unr47xygpfcdvfgyuqgvpzw7be

Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map [article]

Xizhe Xue and Ying Li and Qiang Shen
2020 arXiv   pre-print
Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects.  ...  and color information of the tracked object, and introduce the fused features into a background aware correlation filter to obtain the response map.  ...  The novel fused features are then embedded into a correlation filter that is background-aware (in the sense that the filter is capable of learning from real, negative examples densely extracted from the  ... 
arXiv:2011.12550v1 fatcat:eezvk5ux5fbfboiua5wujv3gwi

Tracking Noisy Targets: A Review of Recent Object Tracking Approaches [article]

Mustansar Fiaz, Arif Mahmood, Soon Ki Jung
2018 arXiv   pre-print
We broadly categorize trackers into correlation filter based trackers and the others as non-correlation filter trackers.  ...  In the second part of this work, we experimentally evaluate tracking algorithms for robustness in the presence of additive white Gaussian noise.  ...  Taxonomy of tracking algorithms Features in Correlation Filter (CF2) for visual tracking.  ... 
arXiv:1802.03098v2 fatcat:2ygcm7gomrgffg3bo6w55kejce

2020 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 28

2020 IEEE/ACM Transactions on Audio Speech and Language Processing  
., +, TASLP 2020 1282-1292 Stochastic Analysis of the Filtered-x LMS Algorithm for Active Noise Con-Cross-Domain Deep Visual Feature Generation for Mandarin Audio-Visual Speech Recognition.  ...  ., +, TASLP 2020 1328-1341 Learning Hierarchy Aware Embedding From Raw Audio for Acoustic Scene Audiovisual Speaker Tracking Using Nonlinear Dynamical Systems With Dynamic Stream Weights.  ...  T Target tracking Multi-Hypothesis Square-Root Cubature Kalman Particle Filter for Speaker Tracking in Noisy and Reverberant Environments. Zhang, Q., +, TASLP 2020 1183 -1197  ... 
doi:10.1109/taslp.2021.3055391 fatcat:7vmstynfqvaprgz6qy3ekinkt4

ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking [article]

Bowen Li, Changhong Fu, Fangqiang Ding, Junjie Ye, Fuling Lin
2021 arXiv   pre-print
Prior correlation filter (CF)-based tracking methods for unmanned aerial vehicles (UAVs) have virtually focused on tracking in the daytime.  ...  The target-aware mask can be applied to jointly train a target-focused filter that assists the context filter for robust tracking.  ...  Target-Aware CF-Based Tracking Target-aware mask aims to highlight important parts within target region for filter training. In [17] , M.  ... 
arXiv:2106.02495v1 fatcat:snsn6cilbfatlkdc7c6xwdwhum

2021 Index IEEE Signal Processing Letters Vol. 28

2021 IEEE Signal Processing Letters  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, LSP 2021 1031-1035 Hybrid Cascade Filter With Complementary Features for Visual Tracking. Zhu, H., +, LSP 2021 86-90 Learning Dynamic Spatial-Temporal Regularization for UAV Object Tracking.  ...  ., +, LSP 2021 1535-1539 Hybrid Cascade Filter With Complementary Features for Visual Tracking. Zhu, H., +, LSP 2021 86-90 Pixel-Attention CNN With Color Correlation Loss for Color Image Denois-ing.  ... 
doi:10.1109/lsp.2022.3145253 fatcat:a3xqvok75vgepcckwnhh2mty74

HKSiamFC: Visual-Tracking Framework Using Prior Information Provided by Staple and Kalman Filter

Chenpu Li, Qianjian Xing, Zhenguo Ma
2020 Sensors  
It models visual tracking as a similarity-learning problem. However, experiments showed that SiamFC was not so robust in some complex environments.  ...  Inspired by the key idea of a Staple tracker and Kalman filter, we constructed two more models to help compensate for SiamFC's disadvantages.  ...  SiamFC models visual tracking as a similarity learning problem, and the CNN in SiamFC is trained end-to-end especially for visual tracking.  ... 
doi:10.3390/s20072137 pmid:32290143 fatcat:ht6bxmlwazh5nozwu2uue5yzra

Learning Future-Aware Correlation Filters for Efficient UAV Tracking

Fei Zhang, Shiping Ma, Lixin Yu, Yule Zhang, Zhuling Qiu, Zhenyu Li
2021 Remote Sensing  
In this paper, we propose a novel future-aware correlation filter tracker, i.e., FACF.  ...  In recent years, discriminative correlation filter (DCF)-based trackers have made considerable progress and drawn widespread attention in the unmanned aerial vehicle (UAV) tracking community.  ...  Failure Cases Conclusions In this work, in order to enhance filter discriminative power in future unknown environments, we proposed a novel future-aware correlation filter tracker, namely FACF.  ... 
doi:10.3390/rs13204111 fatcat:cvhu7aroz5btpm5rpainiejtlu

How to Train Your Differentiable Filter [article]

Alina Kloss, Georg Martius, Jeannette Bohg
2020 arXiv   pre-print
For this, we implement DFs with four different underlying filtering algorithms and compare them in extensive experiments.  ...  Bayesian Filtering algorithms address this state estimation problem, but they require models of process dynamics and sensory observations and the respective noise characteristics of these models.  ...  Overall, we note that learning correlated noise models has a small but consistent positive effect on the tracking performance of all DFs, even when the ground truth noise is not correlated.  ... 
arXiv:2012.14313v1 fatcat:qoxdnrxanbecdbinfbuj7rx7xi

Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments [article]

Ahsan Adeel, Mandar Gogate, Amir Hussain
2018 arXiv   pre-print
For testing, the estimated clean audio features are utilised by the developed novel enhanced visually derived Wiener filter for clean audio power spectrum estimation.  ...  However, at high SNRs or low levels of background noise, visual cues become fairly less effective for speech enhancement.  ...  The contextual AV switching component exploits both audio and visual features to learn the correlation between input (noisy audio and visual features) and output (clean speech) in different noisy scenarios  ... 
arXiv:1808.09825v1 fatcat:wn3ua4uqojaa5doofyizyd3iaq

Deep visual nerve tracking in ultrasound images

Mohammad Alkhatib, Adel Hafiane, Pierre Vieyres, Alain Delbos
2019 Computerized Medical Imaging and Graphics  
While no deep-learning study exists for tracking the nerves in ultrasound images, this paper explores thirteen most recent deep-learning trackers for nerve tracking and presents a comparative study for  ...  However, nerve tracking is a very challenging task that anesthetists can encounter due to the noise, artifacts, and nerve structure variability.  ...  We would like to thank Region Centre Val de Loire for supporting the work.  ... 
doi:10.1016/j.compmedimag.2019.05.007 pmid:31349184 fatcat:ghqphllegvaw3knapi6tl4kgke

Spatio-Temporal Context, Correlation Filter and Measurement Estimation Collaboration Based Visual Object Tracking

Khizer Mehmood, Abdul Jalil, Ahmad Ali, Baber Khan, Maria Murad, Khalid Mehmood Cheema, Ahmad H. Milyani
2021 Sensors  
After the successful detection of occlusion, an extended Kalman filter is used for occlusion handling.  ...  This decreases the chance of tracking failure as the Kalman filter continuously updates itself and the tracking model.  ...  Scale Space Tracking Discriminative correlation filters are widely used in visual object tracking.  ... 
doi:10.3390/s21082841 pmid:33920648 fatcat:vtkxytfvtbc5hbmmksodbryowu
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