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Research on the Correlation Filter Tracking Model Based on the Deep-Pruned Feature Network
Applied Sciences, 2022 Visual tracking is one of the key research fields in computer vision. Based on the combination of correlation filter tracking (CFT) model and deep convolutional neural networks (DCNNs), deep correlation filter tracking (DCFT) has recently become a ...
Honglin Chen, Chunting Li, Chaomurilige
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Multi-channel Correlation Filters [PDF]
2013 IEEE International Conference on Computer Vision, 2013 Modern descriptors like HOG and SIFT are now commonly used in vision for pattern detection within image and video. From a signal processing perspective, this detection process can be efficiently posed as a correlation/ convolution between a multi-channel image and a multi-channel detector/filter which results in a single channel response map indicating
Hamed Kiani Galoogahi +2 more
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Sensors, 2020 Multi-resolution feature fusion DCF (Discriminative Correlation Filter) methods have significantly advanced the object tracking performance. However, careless choice and fusion of sample features make the algorithm susceptible to interference, leading to
Lin Zhou +6 more
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High-Performance Visual Tracking Based on High-Order Pooling Network
IEEE Access, 2022 Convolution Neural Network (CNN) features have been widely used in visual tracking due to their powerful representation. As an important component of CNN, the pooling layer plays a critical role, but the max/average/min operation only explores the first ...
Xinxi Feng, Lei Pu
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IEEE transactions on multimedia, 2022 Many discriminative correlation filter (DCF)-based methods have successfully leveraged the guidance for solving two problems (i.e., the boundary effect and temporal filtering degradation) as a model prior to visual tracking.
Hu Zhu +5 more
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Two-Step Affine Transformation Prediction for Visual Object Tracking
IEEE Access, 2021 The main drawback of correlation filter scheme is that it can only predict translation of the object, ignoring the other affine transformations such as rotation, aspect ratio change, and scale change.
Weiwei Zheng, Huimin Yu, Zhaohui Lu
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Video SAR Moving Target Tracking Using Joint Kernelized Correlation Filter
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Video synthetic aperture radar (ViSAR) has been found very useful for the surveillance of ground moving targets. The target energy can be utilized for ground moving target tracking, while the dynamic shadows of moving targets enable an alternative ...
Chao Zhong, Jinshan Ding, Yuhong Zhang
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Region-filtering correlation tracking [PDF]
Knowledge-Based Systems, 2019 Abstract Correlation filters (CF) have demonstrated a good performance in visual tracking. However, the base training sample region is larger than the object region, including the interference region (IR). IRs in training samples from cyclic shifts of the base training sample severely degrade the quality of the tracking model. In this paper, a region-
Nana Fan +4 more
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Agriculture, 2020 The innovation in science and technical knowledge has prompted an enormous amount of information for the agrarian sector. Machine learning has risen with massive processing techniques to perceive new contingencies in agricultural development.
Dhivya Elavarasan +3 more
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Robust Visual Tracking Based on Adaptive Extraction and Enhancement of Correlation Filter
IEEE Access, 2019 In recent years, correlation filter (CF)-based tracking methods have demonstrated competitive performance. However, conventional CF-based methods suffer from unwanted boundary effects because of the periodic assumption of the training and detection ...
Wuwei Wang, Ke Zhang, Meibo Lv
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