A survey on online learning for visual tracking

• Published in: The Visual computer Vol. 37; no. 5; pp. 993 - 1014
• Main Authors: Abbass, Mohammed Y., Kwon, Ki-Chul, Kim, Nam, Abdelwahab, Safey A., El-Samie, Fathi E. Abd, Khalaf, Ashraf A. M.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2021; Springer Nature B.V
• Subjects: Artificial Intelligence; Artificial neural networks; Cameras; Clutter; Computer Graphics; Computer Science; Computer vision; Data integration; Distance learning; Environment models; Image Processing and Computer Vision; Machine learning; Motion perception; Moving object recognition; Multisensor fusion; Occlusion; Optical tracking; Surveillance; Survey; Unmanned aerial vehicles; Video compression; Deep learning; Real-time computer vision; Object tracking; Convolutional neural networks; Online learning; Particle filter

Visual object tracking has become one of the most active research topics in computer vision, which has been growing in commercial development as well as academic research. Many visual trackers have been proposed in the last two decades. Recent studies of computer vision for dynamic scenes include mo...