Handcrafted and deep trackers: Recent visual object tracking approaches and trends
In recent years, visual object tracking has become a very active research area. An
increasing number of tracking algorithms are being proposed each year. It is because …
increasing number of tracking algorithms are being proposed each year. It is because …
Digital twin: Values, challenges and enablers from a modeling perspective
Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
data and simulators for real-time prediction, optimization, monitoring, controlling, and …
Fuzzy detection aided real-time and robust visual tracking under complex environments
Today, a new generation of artificial intelligence has brought several new research domains
such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot …
such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot …
[HTML][HTML] Improved anti-occlusion object tracking algorithm using Unscented Rauch-Tung-Striebel smoother and kernel correlation filter
R **a, Y Chen, B Ren - Journal of King Saud University-Computer and …, 2022 - Elsevier
Aiming at the existing problems that object tracking algorithm fails to track under the
influence of occlusion conditions, the paper has improved the Kernel Correlation Filter …
influence of occlusion conditions, the paper has improved the Kernel Correlation Filter …
Learning spatial-temporal regularized correlation filters for visual tracking
Abstract Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from
unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to …
unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to …
Visual object tracking with discriminative filters and siamese networks: a survey and outlook
Accurate and robust visual object tracking is one of the most challenging and fundamental
computer vision problems. It entails estimating the trajectory of the target in an image …
computer vision problems. It entails estimating the trajectory of the target in an image …
Discriminative correlation filter with channel and spatial reliability
Short-term tracking is an open and challenging problem for which discriminative correlation
filters (DCF) have shown excellent performance. We introduce the channel and spatial …
filters (DCF) have shown excellent performance. We introduce the channel and spatial …
Multi-cue correlation filters for robust visual tracking
In recent years, many tracking algorithms achieve impressive performance via fusing
multiple types of features, however, most of them fail to fully explore the context among the …
multiple types of features, however, most of them fail to fully explore the context among the …
Learning adaptive discriminative correlation filters via temporal consistency preserving spatial feature selection for robust visual object tracking
With efficient appearance learning models, discriminative correlation filter (DCF) has been
proven to be very successful in recent video object tracking benchmarks and competitions …
proven to be very successful in recent video object tracking benchmarks and competitions …
Crest: Convolutional residual learning for visual tracking
Discriminative correlation filters (DCFs) have\ryn been shown to perform superiorly in visual
tracking. They\ryn only need a small set of training samples from the initial frame to generate …
tracking. They\ryn only need a small set of training samples from the initial frame to generate …