Mr. Jihwan Woo Profile

Jihwan Woo

at SAMSUNG Electronics Co Ltd

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 | 8 February 2015 Paper

Semantic video segmentation using both appearance and geometric information

Jihwan Woo, Kris Kitani, Sehoon Kim, Hantak Kwak, Woosung Shim

Proceedings Volume 9406, 94060B (2015) https://doi.org/10.1117/12.2083165

KEYWORDS: Image segmentation, Video, Optical flow, Image processing algorithms and systems, Semantic video, Detection and tracking algorithms, Visual system, Machine vision, Computer vision technology, Cameras

Read Abstract +

The segmentation is the first step and core technology for semantic understanding of the video. Many tasks in the computer vision such as tracking, recognition and 3D reconstruction, etc. rely on the segmentation result as preprocessing. However, the video segmentation has been known to be a very complicated and hard problem. The objects in the video change their colors and shapes according to the surrounding illumination, the camera position, or the object motion. The color, motion, or depth has been utilized individually as a key clue for the segmentation in many researches. However, every object in the image is composed of several features such as color, texture, depth and motion. That is why single-feature based segmentation method often fails. Humans can segment the objects in video with ease because the human visual system enables to consider color, texture, depth and motion at the same time. In this paper, we propose the video segmentation algorithm which is motivated by the human visual system. The algorithm performs the video segmentation task by simultaneously utilizing the color histogram of the color, the optical flow of the motion, and the homography of the structure. Our results show that the proposed algorithm outperforms other appearance based segmentation method in terms of semantic quality of the segmentation [15]. The proposed segmentation method will serve as a basis for better high-level tasks such as recognition, tracking [3],[4] and video understanding [1].

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