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Visual Tracking is often hindered by difficulties such as occlusion, abrupt motion and out of view problems. Motivated by the wide range of existing features, search mechanisms and target representations, a cooperation strategy between Bayesian tracking and matching by the Binary Robust Invariant Scalable Key-points (BRISK) is devised in this paper. The Bayesian tracker is considered as the main tracker,...
When the signal-to-noise ratio (SNR) is reduced in case of track-before-detect (TBD) for weak target detection, the TBD algorithm based on Gaussian mixture probability hypothesis density (GM-PHD) filter cannot estimate the number or status of targets accurately. In order to solve this problem, a TBD algorithm based on GM-PHD smoothing filter (SGM-PHD-TBD) is proposed. Within the framework of TBD standard...
Feature extractor plays an important role in visual tracking due to the changing appearance of the object. In this paper, we propose a novel approach in correlation filter framework, which decomposes the task of tracking into translation and scale estimation. We employ two correlation filters with hierarchical convolutional features to estimate the translation. Furthermore, we use a discriminative...
We formulate multiple object tracking (MOT) as a Generalized Maximum Multi Clique problem (GMMCP) without any simplified version in problem formulation or optimization, which makes full use of image evidence. Afterwards, we solve the GMMCP through Mixed Binary-Integer Program (MBIP) and obtain the final motion trajectories of the multiple objects. In order to improve the algorithm's performance, we...
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