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Arthur Niswar

dblp:75/7681 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-authorArtificial intelligence and machine learning · 2Human-computer interaction and ubiquitous computing · 1 · 1 first-author

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.

Computer graphics and multimedia
2 papers
Virtual and augmented reality · 72% Computer animation and physical simulation · 17% Geometric modeling and processing · 11%
Artificial intelligence
1 paper
3D vision · 100%

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

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
mixed reality
0.212013
A Mixed Reality Virtual Clothes Try-On System · IEEE Trans. Multim. 2013
Computer vision › 3D vision
3d face reconstruction
0.112010
Pose-invariant 3D face reconstruction from a single image · SIGGRAPH ASIA (Sketches) 2010
Virtual and augmented reality › avatar
avatar customization
0.012013
A Mixed Reality Virtual Clothes Try-On System · IEEE Trans. Multim. 2013
Computer animation and physical simulation
cloth simulation
0.012013
A Mixed Reality Virtual Clothes Try-On System · IEEE Trans. Multim. 2013
Geometric modeling and processing
deformation
0.012010
Pose-invariant 3D face reconstruction from a single image · SIGGRAPH ASIA (Sketches) 2010

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

model-based deformation · 0.2user study · 0.2real-time simulation · 0.2
YearPublicationVenuePosition
2014 SARA - singapore's automated responsive assistant for the touristic domain
Andreea I. Niculescu, Rafael E. Banchs, Ridong Jiang, Seokhwan Kim, Kheng Hui Yeo, Arthur Niswar
INTERSPEECH6
2013 AIDA: Artificial Intelligent Dialogue Agent
Rafael E. Banchs, Ridong Jiang, Seokhwan Kim, Arthur Niswar, Kheng Hui Yeo
SIGDIAL Conference4
2013 A Mixed Reality Virtual Clothes Try-On System
abstract
Virtual try-on of clothes has received much attention recently due to its commercial potential. It can be used for online shopping or intelligent recommendation to narrow down the selections to a few designs and sizes. In this paper, we present a mixed reality system for 3D virtual clothes try-on that enables a user to see herself wearing virtual clothes while looking at a mirror display, without taking off her actual clothes. The user can select various virtual clothes for trying-on. The system physically simulates the selected virtual clothes on the user's body in real-time and the user can see virtual clothes fitting on the her mirror image from various angles as she moves. The major contribution of this paper is that we automatically customize an invisible (or partially visible) avatar based on the user's body size and the skin color and use it for proper clothes fitting, alignment and clothes simulation in our virtual try-on system. We present three scenarios: i) virtual clothes on the avatar, ii) virtual clothes on the user's image and iii) virtual clothes on the avatar blended with the user's face image. We have conducted a user study to evaluate the effectiveness of these three solutions from the end user's perception of quality attributes, cognitive attributes and attitude towards using. The user study shows that among these three scenarios, the second one is most preferred by the users and for 50% of them the experience they had with our system was sufficient to make the purchase decision for the outfits they virtually tried-on.
Miaolong Yuan, Ishtiaq Rasool Khan, Farzam Farbiz, Susu Yao, Arthur Niswar, Min-Hui Foo
IEEE Trans. Multim.5
2010 Pose-invariant 3D face reconstruction from a single image
abstract
This technical sketch presents a novel method to reconstruct 3D face model from only a single image. Different from other methods, ours does not require the face in the image to be in a specific pose. This method deforms a generic 3D face model to fit the shape of the face in the image. The reconstructed 3D face model is then textured using the image. There are many practical applications to this method. For example, it provides a photo-editing tool to change the face pose in the picture as required. It can also be used by the police to investigate the picture of a suspect where only 1 picture is available and it is necessary to have the picture from different poses. Another possible application is entertainment: the 3D face model can be used to personalize character in 3D games.
Arthur Niswar, Ee Ping Ong, Zhiyong Huang 0001
SIGGRAPH ASIA (Sketches)1