AppFusion: Interactive Appearance Acquisition Using a Kinect Sensor

We present an interactive material acquisition system for average users to capture the spatially varying appearance of daily objects. While an object is being scanned, our system estimates its appearance on‐the‐fly and provides quick visual feedback. We build the system entirely on low‐end, off‐the‐...

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Bibliographic Details
Published in:Computer graphics forum Vol. 34; no. 6; pp. 289 - 298
Main Authors: Wu, Hongzhi, Zhou, Kun
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.09.2015
Subjects:
Acquisitions
Analysis
appearance modelling
Computation
Computer graphics
Computer peripherals
Estimates
Feedback
I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism-Colour
Image processing systems
Interactive
Marketing
Roughness
Sensors
shading
shadowing and texture
Studies
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary:We present an interactive material acquisition system for average users to capture the spatially varying appearance of daily objects. While an object is being scanned, our system estimates its appearance on‐the‐fly and provides quick visual feedback. We build the system entirely on low‐end, off‐the‐shelf components: a Kinect sensor, a mirror ball and printed markers. We exploit the Kinect infra‐red emitter/receiver, originally designed for depth computation, as an active hand‐held reflectometer, to segment the object into clusters of similar specular materials and estimate the roughness parameters of BRDFs simultaneously. Next, the diffuse albedo and specular intensity of the spatially varying materials are rapidly computed in an inverse rendering framework, using data from the Kinect RGB camera. We demonstrate captured results of a range of materials, and physically validate our system. We present an interactive material acquisition system for average users to capture the spatially varying appearance of daily objects. While an object is being scanned, our system estimates its appearance on‐the‐fly and provides quick visual feedback. We build the system entirely on low‐end, off‐the‐shelf components: a Kinect sensor, a mirror ball and printed markers. We exploit the Kinect infra‐red emitter/receiver, originally designed for depth computation, as an active hand‐held reflectometer, to segment the object into clusters of similar specular materials and estimate the roughness parameters of BRDFs simultaneously.
Bibliography:ark:/67375/WNG-S8ZSM555-C
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12600