Prof. Liyan Zhang Profile

Prof. Liyan Zhang

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 27 January 2021 Paper

Multi-stage analysis for long-term tracking

Lizhi Bai, Liyan Zhang

Proceedings Volume 11720, 117200I (2021) https://doi.org/10.1117/12.2589391

Read Abstract +

In long-term visual object tracking, the tracking model would be prone to drift or corruption and the tracker can hardly catch the target again after tracking failures. A set of novel strategies for long-term tracking is proposed to solve these problems. First, a simple and efficient method is proposed to calculate the tracking confidence of Staple, a well-known tracker based on correlation filers. A model update mechanism is then developed to prevent model corruption. Furthermore, an online Support Vector Machine (SVM) classifier is trained to re-detect the object in case of unreliable tracking result. By means of intermittent sampling in the re-detection stage, the computational efficiency and the re-detection reliability are greatly improved. The combination of these new components in multi-stages spawns a real-time, accurate and robust tracker for long-term video. Experimental results demonstrate that our tracker, operating at a speed of 30 FPS, performs superiorly against some competitive trackers on robustness and accuracy, especially when the target encounters occlusion, severe deformation and out-of-view.

Proceedings Article | 13 April 2018 Paper

Laser projection positioning of spatial contour curves via a galvanometric scanner

Junchao Tu, Liyan Zhang

Proceedings Volume 10696, 1069625 (2018) https://doi.org/10.1117/12.2309485

KEYWORDS: 3D modeling, Control systems, Systems modeling, Laser scanners, 3D scanning, Computer aided design, Calibration, Solid modeling, Neurons, Visual process modeling

Read Abstract +

The technology of laser projection positioning is widely applied in advanced manufacturing fields (e.g. composite plying, parts location and installation). In order to use it better, a laser projection positioning (LPP) system is designed and implemented. Firstly, the LPP system is built by a laser galvanometric scanning (LGS) system and a binocular vision system. Applying Single-hidden Layer Feed-forward Neural Network (SLFN), the system model is constructed next. Secondly, the LGS system and the binocular system, which are respectively independent, are integrated through a datadriven calibration method based on extreme learning machine (ELM) algorithm. Finally, a projection positioning method is proposed within the framework of the calibrated SLFN system model. A well-designed experiment is conducted to verify the viability and effectiveness of the proposed system. In addition, the accuracy of projection positioning are evaluated to show that the LPP system can achieves the good localization effect.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years