Intrinsic Decomposition of Image Sequences from Local Temporal Variations

We present a method for intrinsic image decomposition, which aims to decompose images into reflectance and shading layers. Our input is a sequence of images with varying illumination acquired by a static camera, e.g. an indoor scene with a moving light source or an outdoor timelapse. We leverage the...

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Bibliographic Details
Main Authors: Laffont, Pierre-Yves, Bazin, Jean-Charles
Format: Conference Proceeding
Language:English
Subjects:
Computer vision
Conferences
Decomposition
Geometry
Illumination
Image color analysis
Image decomposition
Image sequences
Light sources
Lighting
Reflectance
Reflectivity
Robustness
Shading
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Description
Summary:We present a method for intrinsic image decomposition, which aims to decompose images into reflectance and shading layers. Our input is a sequence of images with varying illumination acquired by a static camera, e.g. an indoor scene with a moving light source or an outdoor timelapse. We leverage the local color variations observed over time to infer constraints on the reflectance and solve the ill-posed image decomposition problem. In particular, we derive an adaptive local energy from the observations of each local neighborhood over time, and integrate distant pairwise constraints to enforce coherent decomposition across all surfaces with consistent shading changes. Our method is solely based on multiple observations of a Lambertian scene under varying illumination and does not require user interaction, scene geometry, or an explicit lighting model. We compare our results with several intrinsic decomposition methods on a number of synthetic and captured datasets.
ISSN:2380-7504
DOI:10.1109/ICCV.2015.57