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Markerless Real-Time Garment Retexturing From Monocular 3D Reconstruction

Markerless Real-Time Garment Retexturing From Monocular 3D Reconstruction
Markerless Real-Time Garment Retexturing From Monocular 3D Reconstruction
We present a fusion of augmented reality (AR) and virtual try on (VTO) that incorporates sparse 3D point recovery by exploiting distance constraints based on 2D point correspondences between a deformed texture in monocular video and a reference texture which is derived from the start of the sequence by face detection aided segmentation. A hierarchical and multi-resolution surface reconstruction approach is proposed, employing thin-plate splines, cloth modeling, and patch tessellation. Our method attempts to accurately recover a rectangular surface from a deformed arbitrarily shaped texture. We also propose a hue-based method for segmenting garment cloth and printed texture. The methods are demonstrated in an AR framework for real-time visualization of a virtual garment worn in a real scene. Real-time AR cloth retexturing from monocular vision is a state-of-the-art field. Previous work lacks realism and accuracy, only recovering the 2D cloth layout and lacks robustness, requiring a special T-shirt color and simple texture along with lab hardware. Our approach alleviates these limitations. We design a practical approach which considers a typical consumer environment with a mid-range PC and webcam. Our results are convincing and photorealistic with robustness to arbitrary T-shirts, subjects, and backgrounds. Future work will focus on extending our global model and quantitative analysis.
Cushen, George
52f73d41-3ae0-4c11-a50a-86e782c03745
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Cushen, George
52f73d41-3ae0-4c11-a50a-86e782c03745
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Cushen, George and Nixon, Mark (2011) Markerless Real-Time Garment Retexturing From Monocular 3D Reconstruction. IEEE International Conference on Signal and Image Processing Applications (ICSIPA), Malaysia.

Record type: Conference or Workshop Item (Paper)

Abstract

We present a fusion of augmented reality (AR) and virtual try on (VTO) that incorporates sparse 3D point recovery by exploiting distance constraints based on 2D point correspondences between a deformed texture in monocular video and a reference texture which is derived from the start of the sequence by face detection aided segmentation. A hierarchical and multi-resolution surface reconstruction approach is proposed, employing thin-plate splines, cloth modeling, and patch tessellation. Our method attempts to accurately recover a rectangular surface from a deformed arbitrarily shaped texture. We also propose a hue-based method for segmenting garment cloth and printed texture. The methods are demonstrated in an AR framework for real-time visualization of a virtual garment worn in a real scene. Real-time AR cloth retexturing from monocular vision is a state-of-the-art field. Previous work lacks realism and accuracy, only recovering the 2D cloth layout and lacks robustness, requiring a special T-shirt color and simple texture along with lab hardware. Our approach alleviates these limitations. We design a practical approach which considers a typical consumer environment with a mid-range PC and webcam. Our results are convincing and photorealistic with robustness to arbitrary T-shirts, subjects, and backgrounds. Future work will focus on extending our global model and quantitative analysis.

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More information

Published date: November 2011
Venue - Dates: IEEE International Conference on Signal and Image Processing Applications (ICSIPA), Malaysia, 2011-11-01
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 273103
URI: http://eprints.soton.ac.uk/id/eprint/273103
PURE UUID: 239584cf-7c4a-474b-9f96-722bb27de9a5
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 15 Jan 2012 12:20
Last modified: 26 Nov 2019 02:08

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