A more stable and robust approach is proposed for visual tracking relying on Maximally Stable Extremal Regions (MSERs), sparse random projection and online ...

The contribution of this paper is that we proposed a more stable and robust compressive tracking algorithm via sparse random projection based on the stable ...

The compressed tracking algorithm (CT tracker) is a well-known visual tracking method that models a target object's appearance through sparse random ...

The compressed tracking algorithm (CT tracker) is a well-known visual tracking method that models a target object׳s appearance through sparse random ...

The compressed tracking algorithm (CT tracker) is a well-known visual tracking method that models a target object׳s appearance through sparse random projection.

Aug 19, 2021 · The study demonstrates that the random project algorithm is a promising method to generate optimal feature vectors to help improve performance of machine ...

Tian, “Extended compressed tracking via random projection based on msers and online ls-svm learning,” Pattern Recognition, vol. 59, pp. 245–254, 2016. [92] ...

In this paper, we propose a novel approach that uses analytical expressions to exactly update the LS-SVM model using the added and deleted data samples only.

A method for predicting the optimal vibration field parameters by least square support vector machine (LS-SVM) is presented in this paper.

Apr 17, 2019 · Tian, ''Extended compressed tracking via random projection based on MSERs and online. LS-SVM learning,'' Pattern Recognit., vol. 59, pp. 245 ...