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Younglae J. Bae

dblp:30/2626 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Interaction techniques and input · 90% Immersive interaction · 10%
Computer graphics and multimedia
2 papers
Multimedia analysis and retrieval · 64% Virtual and augmented reality · 36%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › navigation
3d navigation		 0.012000
Touring into the picture using hand shape recognition (poster session) · ACM Multimedia 2000
Interaction techniques and input
gesture input		 0.012000
Touring into the picture using hand shape recognition (poster session) · ACM Multimedia 2000
Immersive interaction
3d user interface		 0.012000
Touring into the picture using hand shape recognition (poster session) · ACM Multimedia 2000

Methods — techniques the papers use, named apart from their topics

interactive similarity retrieval · 0.1hand shape gesture recognition · 0.12d-to-3d image conversion · 0.1
YearPublicationVenuePosition
2004 Image Navigation: A Massively Interactive Model for Similarity Retrieval of Images
Seyoon Jeong, Kyuseo Han, Byungtae Chun, Younglae J. Bae
 Int. J. Comput. Vis.5
2001 Hand gesture recognition using combined features of location, angle and velocity
Ho-Sub Yoon, Jung Soh, Younglae J. Bae, Hyun Seung Yang
 Pattern Recognit.3
2000 Touring into the picture using hand shape recognition (poster session)
abstract
The purpose of this study is to prove that using gesture recognition through implementing the method of touring into the picture makes navigation very convenient and easy compared to navigation using mouse and keyboard. The method of touring into the picture is a simple technique that converts an 2D image into 3D animation. This study shows how to convert 2D image into 3D navigation, implementing the method previously proposed by Horry and Phy on the personal computer. Hand shape gesture recognition which functions as a user interface has been developed into three types: Type-1 means pause, Type-2 means showing directions on 2D; Type-3 is designed to assign upper and lower depth in space. These three types play the role as virtual mouse and keyboard in 3D-rendering image. Above all, using hand-shaped gestures contributes to the ease of user's navigation of 3D space..
Eu-Mi Ji, Ho-Sub Yoon, Younglae J. Bae
 ACM Multimedia3