Generalization of the Lambertian model and implications for machine vision

Oren, Michael B.; Nayar, Shree K.

doi:10.1007/bf01679684

Cited by 396 publications

(220 citation statements)

References 22 publications

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“…So the imaging lens whose angle of axis and the normal is 45°can only receive the diffuse reflection light. Based on the micro-surface model proposed by Oren and Nayar [13], the region receiving light of the measured surface can be divided into many micro-surfaces. The diffuse reflection light of each micro-surface follows Lambert Law:…”

Section: Theoretical Analysesmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Standard Deviation and Reflectance of the Measured Surface on Laser Diode-Position Sensitive Detector System

Song

Xia

Wang

2016

MATEC Web of Conferences

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Abstract. For improving the accuracy and applicability of laser diode-position sensitive detector (LD-PSD) system, a model of roughness and reflectance of the measured surface is established. Combining this model with the light intensity response model of PSD and the space radiation model, we derived the relationship between the standard deviation (ı), reflectance (ȡ) and the center-of-gravity of light intensity (X 0 ). This relationship shows that X 0 is disturbed by ı or ȡ only if ı or ȡ changes within the spot. We conducted a simulation and experiment to test this relationship. The results showed a good consistency with the theory, which proved that the variation of ı and ȡ can greatly impact the accuracy and robustness of LD-PSD system, and a smaller light spot can improve this situation.

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Section: Theoretical Analysesmentioning

confidence: 99%

“…r i E T T (13) where the definitions of ș i , ș r , ĳ i and ĳ r are shown in Figure 3, ı is the standard deviation of Gaussian distribution micro-surfaces, which is used to characterize the surface roughness [15][16][17][18][19]. In Ld-PSD system shown in Figure1, it can be derived that:…”

Section: Theoretical Analysesmentioning

confidence: 99%

Impact of Standard Deviation and Reflectance of the Measured Surface on Laser Diode-Position Sensitive Detector System

Song

Xia

Wang

2016

MATEC Web of Conferences

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“…The methods used to model or approximate the BRDF can be divided into those that are physics-based, semi-empirical [37,53] or empirical [25,38,45] in nature. Although the literature from physics is vast, it is perhaps the work of Beckmann on smooth and rough surface reflectance that is better known in the vision and graphics communities [2].…”

Section: Introductionmentioning

confidence: 99%

An optimisation approach to the recovery of reflection parameters from a single hyperspectral image

Rahman

Robles-Kelly

2013

Computer Vision and Image Understanding

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In this paper, we present a method to recover the parameters governing the reflection of light from a surface making use of a single hyperspectral image. To do this, we view the image radiance as a combination of specular and diffuse reflection components and present a cost functional which can be used for purposes of iterative least squares optimisation. This optimisation process is quite general in nature and can be applied to a number of reflectance models widely used in the computer vision and graphics communities. We elaborate on the use of these models in our optimisation process and provide a variant of the Beckmann-Kirchhoff model which incorporates the Fresnel reflection term. We show results on synthetic images and illustrate how the recovered photometric parameters can be employed for skin recognition in real world imagery, where our estimated albedo yields a classification rate of 95.09 ± 4.26% as compared to an alternative, whose classification rate is of 90.94 ± 6.12%. We also show quantitative results on the estimation of the index of refraction, where our method delivers an average per-pixel angular error of 0.15 degrees. This is a considerable improvement with respect to an alternative, which yields an error of 9.9 degrees.

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“…A BRDF is traditionally measured by using gonio-reflectometers, custom built devices which are expensive [1] and suffer from practical limitations such as angular precision and measurement noise. Some of these limitations can be overcome by employing reflectance models such as Lambertian [2], Phong [3], TorranceSparrow [4], Oren-Nayar [5] and more recently a tensor-spline based approach [6], and indeed, these have been used with great success. However, modelling is no substitute for the use of an accurate, image-based BRDF to capture the subtleties of the reflectance properties of an object.…”

Section: Introductionmentioning

confidence: 99%