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Multiview latent space learning with feature redundancy minimization
Multiview learning has received extensive research interest and has demonstrated
promising results in recent years. Despite the progress made, there are two significant …
promising results in recent years. Despite the progress made, there are two significant …
Entropy based dictionary learning for image classification
In this paper, a new discriminative dictionary learning algorithm is introduced. An entropy
based criterion is embedded into the objective function to enforce a proper structure for the …
based criterion is embedded into the objective function to enforce a proper structure for the …
Learning transform-aware attentive network for object tracking
Existing trackers often decompose the task of visual tracking into multiple independent
components, such as target appearance sampling, classifier learning, and target state …
components, such as target appearance sampling, classifier learning, and target state …
Hybridizing teaching-learning-based optimization with adaptive grasshopper optimization algorithm for abrupt motion tracking
Aiming at the problem that conventional tracking algorithms are difficult to deal with abrupt
motion efficiently, an optimization algorithm called hybrid Teaching-learning-based …
motion efficiently, an optimization algorithm called hybrid Teaching-learning-based …
Visual tracking with levy flight grasshopper optimization algorithm
Grasshopper optimization algorithm (GOA) is a new meta-heuristic optimization algorithm
that it simulates behavior of grasshopper swarms in nature. In this paper, a tracking …
that it simulates behavior of grasshopper swarms in nature. In this paper, a tracking …
Abnormal behavior detection using sparse representations through sequentialgeneralization of k-means
The potential capability to automatically detect and classify human behavior as either normal
or abnormal events is an important aspect in intelligent monitoring/surveillance systems …
or abnormal events is an important aspect in intelligent monitoring/surveillance systems …
Robust object tracking based on adaptive multicue feature fusion
Object tracking is challenging due to unconstrained variations in the target's appearance
and complex environmental variations. Appearance models based on a single cue are …
and complex environmental variations. Appearance models based on a single cue are …
Multi-view coupled dictionary learning for person re-identification
In recent years, person re-identification is becoming an important technique, which can be
applied in computer vision, pedestrian tracking and intelligent monitoring. Due to the large …
applied in computer vision, pedestrian tracking and intelligent monitoring. Due to the large …
Discriminative Deep Non-Linear Dictionary Learning for Visual Object Tracking
Deep neural networks have been widely applied to visual tracking and obtained significant
improvements in tracking accuracy and robustness. But some algorithms of this kind suffer …
improvements in tracking accuracy and robustness. But some algorithms of this kind suffer …
Uncertain motion tracking combined markov chain monte carlo and correlation filters
H Zhang, G Nie, J Chen, J Zhang, G Yang - IEEE Access, 2019 - ieeexplore.ieee.org
To address the uncertain motion tracking problem, a tracking method based on the Markov
Chain Monte Carlo and correlation filters is proposed. Firstly, multi-scope marginal …
Chain Monte Carlo and correlation filters is proposed. Firstly, multi-scope marginal …