Object Tracking in Video Using the TLD and CMT Fusion Model

Dublin Core

Title

Object Tracking in Video Using the TLD and CMT Fusion Model

Subject

Object Tracking, Tracking-Learning-Detection (TLD), Clustering of Static-Adaptive Correspondences for Deformable Object Tracking (CMT).

Description

Object tracking has been an attractive study topic in computer vision in recent years, thanks to the development of video monitoring systems. Tracking-Learning Detection (TLD), Compressive Tracking (CT), and Clustering of Static-Adaptive Correspondences for Deformable Object Tracking are some of the state-of-the-art methods for motion object tracking (CMT). We present a fusion model that combines TLD and CMT in this study. To restrict the calculation time of the CMT technique, the fusion TLD CMT model enhanced the TLD benefits of computation time and accuracy on t no deformable objects. The experimental results on the Vojir dataset for three techniques (TLD, CMT, and TLD CMT) demonstrated that our fusion proposal successfully trades off CMT accuracy for computing time.

Creator

Hai Tran

Source

www.ijcit.com

Date

September 2021

Contributor

peri irawan

Format

pdf

Language

english

Type

text

Files

Citation

Hai Tran, “Object Tracking in Video Using the TLD and CMT Fusion Model,” Repository Horizon University Indonesia, accessed June 1, 2025, https://repository.horizon.ac.id/items/show/9007.