Estimating reflection parameters from a single color image

Tominaga, Shoji; Tanaka, Norihiro

doi:10.1109/38.865881

Cited by 58 publications

(34 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Sato et al [1] and Tominaga et al [2] estimated shape, texture, and surface roughness. Zheng et al [3], Nayar et al [4], and Kim et al [5] estimated shape, texture, and illumination distribution.…”

Section: Introductionmentioning

confidence: 99%

Polarization-based inverse rendering from a single view

Miyazaki

Tan

Hara

et al. 2003

Proceedings Ninth IEEE International Conference on Computer Vision

163

107

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Polarization-based inverse rendering from a single view

Miyazaki

Tan

Hara

et al. 2003

Proceedings Ninth IEEE International Conference on Computer Vision

163

107

View full text Add to dashboard Cite

show abstract

“…With known geometry of the scene, Sato et al [41] have utilised brightness values within shadows to solve a system of equations to simultaneously recover reflectance parameters and illumination distribution. Tominaga et al [48] have proposed a method for estimating various reflection parameters of the Phong reflectance model [38] along with shape, illumination direction and color from a single image.…”

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

View full text Add to dashboard Cite

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.

show abstract

“…This is a challenging problem as it implies the registration of 3D to 2D data from different sensors with certain degrees of deformation. Intensity based techniques based on mutual information [3,4] or cross correlation can be problematic due to deformation and the difficulties in accurately modeling of illuminations [5,6]. Endoscopic images are illuminated by a light source very close to the internal wall and are heavily affected by inter-reflections.…”

Section: Introductionmentioning

confidence: 99%

pq-Space Based 2D/3D Registration for Endoscope Tracking

Deligianni

Chung

Yang

2003

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. This paper presents a new pq-space based 2D/3D registration method for camera pose estimation for endoscope tracking. The proposed technique involves the extraction of surface normals for each pixel of the video images by using a linear local shape-from-shading algorithm derived from the unique camera/lighting constrains of the endoscopes. We illustrate how to use the derived pq-space distribution to match to that of the 3D tomographic model, and demonstrate the accuracy of the proposed method by using an electro-magnetic tracker and a specially constructed airway phantom. Comparison to existing intensity-based techniques has also been made, which highlights the major strength of the proposed method in its robustness against illumination and tissue deformation.

show abstract

Estimating reflection parameters from a single color image

Cited by 58 publications

References 10 publications

Polarization-based inverse rendering from a single view

Polarization-based inverse rendering from a single view

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

pq-Space Based 2D/3D Registration for Endoscope Tracking

Contact Info

Product

Resources

About