Mr. Xuan Qi Profile

Xuan Qi

at Clarkson Univ

SPIE Involvement:

Author

Publications (1)

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 | 23 April 2020 Presentation + Paper

Compression artifact mitigation for face in video recognition

Xuan Qi, Chen Liu

Proceedings Volume 11419, 114190M (2020) https://doi.org/10.1117/12.2556702

KEYWORDS: Video compression, Video, Facial recognition systems, Feature extraction, Image restoration, Image compression, Video acceleration, Super resolution, Video surveillance, Convolution

Read Abstract +

Face in video recognition (FiVR) is widely used in video surveillance and video analytic. Various solutions have been proposed to improve the performance of face detection, frame selection and face recognition in FiVR systems. However, all these methods have a common inherent ceiling", which is defined by the source video's quality. One key factor causing face image quality loss is video compression standards. To address this challenge, in this paper, first, we analysis and quantify the effects of video compression on the FiVR performance; secondly, we propose to use deep learning based model to mitigate artifacts in compressed input video. We apply the image based convolutional auto-encoder (CAE) to extract the features of input face images and restore them towards less artifacts. From the experimental results, our approach can mitigate artifacts on face images extracted from compressed videos and improve the overall face recognition (FR) performance by as much as 50% in TPR (True Positive Rate) at the same FPR (False Positive Rate) value.

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