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We present a method for decomposing an image into its intrinsic reflectance and shading components. Different from previous work, our method examines texture information to obtain constraints on reflectance among pixels that may be distant from one another in the image. We observe that distinct points with the same intensity-normalized texture configuration(More)
We propose a method for intrinsic image decomposition based on retinex theory and texture analysis. While most previous methods approach this problem by analyzing local gradient properties, our technique additionally identifies distant pixels with the same reflectance through texture analysis, and uses these nonlocal reflectance constraints to significantly(More)
We present an appearance-based user interface for artists to efficiently design customized image-based lighting environments. 1 Our approach avoids typical iterations of parameter editing, rendering, and confirmation by providing a set of intuitive user interfaces for directly specifying the desired appearance of the model in the scene. Then the system(More)
We extend photometric stereo to make it work with internet images, which are typically associated with different viewpoints and significant noise. For popular tourism sites, thousands of images can be obtained from internet search engines. With these images, our method computes the global illumination for each image and the surface orientation at some scene(More)
Intrinsic image decomposition is an important problem that targets the recovery of shading and reflectance components from a single image. While this is an ill-posed problem on its own, we propose a novel approach for intrinsic image decomposition using reflectance sparsity priors that we have developed. Our sparse representation of reflectance is based on(More)
The present paper focuses on efficient inverse rendering using a photometric stereo technique for realistic surfaces. The technique primarily assumes the Lambertian reflection model only. For non-Lambertian surfaces, application of the technique to real surfaces in order to estimate 3D shape and spatially varying reflectance from sparse images remains(More)
Monitoring aspects of human performance during various activities has recently become a highly investigated research area. Many new commercial products are available now to monitor human physical activity or responses while performing activities ranging from playing sports, to driving, and even sleeping. However, monitoring cognitive performance biomarkers,(More)
A major challenge in inverse reflectometry is the acquisition of spatially varying materials. In this paper, we introduce a method to recover spatial reflectance from a sparse set of images under general illumination. Specifically, we first remove the high-frequency varying diffuse reflection term by using a low-order spherical harmonic approximation. This(More)
— In many applications it is desirable to simultaneously measure the concentration of multiple fluorescent sources. In this paper, a simple robust technique for accomplishing this is realized by illuminating the fluorescent elements by excitation light modulated at different frequencies. A single microprocessor is used to drive the excitation sources(More)