Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Surface Reflection: Physical and Geometrical Perspectives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining Reflectance Properties of an Object Using Range and Brightness Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color Reflectance Modeling Using a Polychromatic Laser Range Sensor
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Measuring and modeling anisotropic reflection
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Efficient eigenvalues for visualization
Graphics gems IV
Inverting an illumination model from range and intensity maps
CVGIP: Image Understanding
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Reflectance analysis for 3D computer graphics model generation
Graphical Models and Image Processing
Reliable Surface Reconstructiuon from Multiple Range Images
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Reflectance function estimation and shape recovery from image sequence of a rotating object
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
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An object model for computer graphics applications should contain two aspects of information: shape and reflectance properties of the object. A number of techniques have been developed for modeling object shapes by observing real objects. In contrast, attempts to model reflectance properties are too simple or too complicated to be used for synthesizing realistic images of the object. In this paper, we propose a new method for modeling object reflectance properties, as well as object shapes, by observing real objects. First, an object surface shape is reconstructed by merging multiple range images of the object. By using the reconstructed object shape and a sequence of color images of the object, parameters of a reflection model are estimated in a robust manner. The key point of the proposed method is that, first, the diffuse and specular reflection components are separated from the color image sequence, and then, reflectance parameters of each reflection component are estimated separately. This approach enables estimation of reflectance properties of real objects whose surfaces show specularity as well as diffusely reflected lights. The recovered object shape and reflectance properties are then used for synthesizing object images with realistic shading effects under arbitrary illumination conditions.