… This study addresses the tracking–learning–detection (TLD) algorithm for long-term
single-target tracking of moving vehicle from video streams. The problems leading to …

… Most sparse coding-based discriminative object tracking methods [15] learn dictionary and
… In the future, we will attempt to extend our method to multiple target tracking with multitask …

… , there is only one positive training sample at the beginning of visual object tracking, but we
have to model a robust classifier on-the-fly. Although there are little positive training samples, …

… We mainly focused on the learning rate and reliable patch to update the target model. To
select the reliable target appearance and dynamic learning rate, we computed the peak-to-…

… Inspired by the method [44], we develop a novel visual object tracking method based on
tracking-learning-detection framework and MSSTResNet feature model. In contrast to previous …

… In this paper, we have proposed an automatic robust realtime object tracking approach that
is able to adapt to variations in shape and size of the object as well as track the airplanes, …

… Abstract—In order to improve the robustness and the speed of single target tracking, this
paper proposes an improved Tracking Learning Detection method. By modifying the …

… In this paper, we present a novel hybrid model of CNN and extreme learning machine (ELM)
for object tracking. Training a conventional CNN requires a substantial amount of …

… Over the past years several methods have been proposed for object tracking and this
section summarizes the ones related with our model. Existing methods can be categorized as …

… robustness and speed of single target tracking, this paper proposes an improved tracking …
The purpose is to improve the tracking module in the traditional tracking learning detection (…