Bispectral Photometric Stereo based on Fluorescence
Imari Sato
National Institute of Informatics
Tokyo, Japan

Takahiro Okabe, Yoichi Sato
University of Tokyo
Tokyo, Japan

imarik@nii.ac.jp

takahiro,ysato@iis.u-tokyo.ac.jp

Abstract
We propose a novel technique called bispectral photometric stereo that makes effective use of fluorescence forshape reconstruction. Fluorescence is a common phenomenon occurring in many objects from natural gems andcorals, to fluorescent dyes used in clothing. One of theimportant characteristics of fluorescence is its wavelengthshifting behavior: fluorescent materials absorb light at
a certain wavelength and then reemit it at longer wavelengths. Due to the complexity of its emission process, fluorescence tends to be excluded from most algorithms in computer vision and image processing. In this paper, we showthat there is a strong similarity between fluorescence andideal diffuse reflection and that fluorescence can provide
distinct clues on how to estimate an object’s shape. Moreover, fluorescence’s wavelength-shifting property enables
us to estimate the shape of an object by applying photometric stereo to emission-only images without suffering from
specular reflection. This is the significant advantage of thefluorescence-based method over previous methods based onreflection.

Figure 1. Reflective and fluorescent components separated throughbispectral measurement: image of a cutter under near UV light(left), fluorescent-only image observed in the red channel (middle), and reflective-component-only images observed in the blue
channel of the camera (right).

computer vision and image processing. In this paper, weshow that fluorescence has the potential of providing clues
for estimating an object’s surface normals and present a
novel photometric stereo approach based on fluorescenceobserved by a technique called bispectral measurement
wherein the incident and received wavelengths are different. The reflective component is seen only when the incident and outgoing wavelengths are the same, and this allows us to obtain emission-only images by simply setting
a longer wavelength than the incident one as the received
wavelength.
The classical photometric stereo approach [27] recovers the shape of an object having Lambertian reflectancefrom multiple images taken of it under known light sources.
Although photometric stereo has been intensively studied
to cope with objects having complex appearances and/or
deal with illuminations from unknown directions, most approaches focus on the reflections from the object’s surface,and no attention has been paid to the re-radiation (emission) of an object’s fluorescent materials. In this work, we
propose to use fluorescence from an object containing both
non-fluorescent and fluorescent materials for shape reconstruction. In fact, there is a strong similarity between the
fluorescence emission and the ideal diffuse reflection.
Wilkie et al. used this fact for modeling fluorescent emissions as diffuse reflections with a wavelength-shifting property, i.e., a diffuse surface that reflects light at a wavelength
different from the incident one [25]. Their development mo-

1. Introduction
Fluorescence emission is a common phenomenon occurring in many objects from natural gems and corals,
to fluorescent dyes used for clothing; even laundry detergent contains fluorescence dyes to brighten/whiten clothing.
Through intensive studies on color constancy algorithms,
Barnard concluded that fluorescent surfaces are common
and present in 20 % of randomly constructed scenes [2].
What makes fluorescence different from ordinary reflectionis the transfer of energy from one wavelength to another.
More specifically, fluorescent materials absorb light at a certain wavelength and then reemit it at other wavelengths after about 10−8 seconds, whereas ordinary reflective components reflect light at the same wavelength as incident.
Due to the complexity of its emission process, fluorescence tends to be excluded from most algorithms in1

tivated us to create a new method for shape reconstruction
based on fluorescence observed by bispectral measurement.
As far as we know, this is the first attempt to use fluorescence from an object for estimating its surface normals.
Fluorescence measured bispectrally provides the following advantages for photometric stereo. First, by simply
having different incident and received wavelengths, we can
avoid observing reflections including troublesome specularreflection and utilize emission-only images for shape reconstruction. For instance, Figure 1 shows the reflective andfluorescent components of an object separated through bispectral measurement. We see that fluorescent-only image
observed under near UV light in the red channel of a camera
is free from specularity (Figure 1 middle). Secondly, interreflections caused by fluorescence emissions are much lessthan those caused by diffuse reflections: a fluorescent material will not be excited much by its own emission. Specularreflection and interreflection often decrease the accuracy of
shape reconstruction. The use of emission-only images has
significant advantages over previous methods based on reflection. The contributions of our paper are• presenting a bispectal radiance equation that describes
the brightness changes of an object containing both
non-fluorescent and fluorescent components under different lighting directions,• using bispectral measurement for separating reflective
and fluorescent components, and• presenting a new approach for photometric stereo
based on fluorescence emission.
The rest of the paper is structured as follows. Section 2
summarizes research on photometric stereo and on color appearance and rendering algorithms for fluorescent surfaces.
Section 3 describes the characteristics of fluorescence andpresents the bispectral radiance equation that represents theappearance of a composite object containing both ordinaryreflective and fluorescent components. We discuss the advantages of using the fluorescence captured by bispectral
measurements in Section 4 and then present our bispectral
photometric stereo method in Section 5. Experiments onreal images of composite objects are presented in Section
6. In the conclusion, we discuss the future directions of ourresearch.

2. Related Work
Shape recovery using photometric stereo. The classicalphotometric stereo approach [27] recovers the shape of an
object having Lambertian reflectance from multiple imagesof it taken under known light sources. Later, this approach
was extended to include a broader range of circumstancessuch as non-Lambertian surfaces[16, 8, 22, 11, 29, 4](for a good overview, see [26]), and uncalibrated photometric stereo [13, 6, 5] (for the cases of unknown lightsources). Some researchers studied the effect of interreflection between object surfaces for shape reconstruction[20, 7, 21, 18].
While many techniques have been proposed for solving
different problems, almost all of them exploit only reflections from the object’s surface. Our approach differs fromthese approaches in that we do not use reflection at all but
rather utilize fluorescent emissions (reradiation by fluorescent materials) observed bispectrally.
Fluorescence. The apparent color of non-fluorescent surfaces has been intensively studied in color-related computer
vision algorithms. Barnard compared various color constancy algorithms with a large set of test images that included some images of fluorescent objects [3]. The evaluated algorithms however treated fluorescence as being composed of ordinary reflective components. Later, Barnard
proposed ways to improve color constancy algorithms sothat they could deal with spectral data of several fluorescentmaterials [2]. There have also been studies on separating thereflective and fluorescent components observed in composite objects [19, 28]. Alterman et al. separated the appearances of individual fluorescent dyes to analyze underlying
mixture of materials by unmixing multiplexed images [1].
Researchers in the field of computer graphics havealso realized that assuming all objects are non-fluorescentgreatly limits the quality of the rendered objects because
many objects in the real world exhibit fluorescence. Glassner first incorporated the wavelength-shifting property offluorescence into Kajiya’s rendering equation [12]. Johnson
and Fairchild provided brief explanations of fluorescencephenomena and extended spectral rendering algorithms totake fluorescence into account [17].
Bispectral methods are often used for modeling fluorescence emissions in the field of fluorometry, in which thespectral distribution of the fluorescence is measured as afunction of the incident and outgoing wavelengths: Donaldson’s re-radiation matrices are used for representing fluorescent spectral radiation factors whose elements are defined by the incident and outgoing wavelengths [9]. Purefluorescent material has no directional characteristics [12],and fluorescence radiance factors are often captured witha fixed measurement geometry, e.g., 0◦ /45◦ or 0◦ /10◦ forincident and received light and vice versa.
Later, Wilkie et al. showed that even a fluorescent diffuse
sheet contains a small but significant amount of specularitythat produces some directional dependence in its appearance [25], and they represented its appearance as a combination of fluorescent and non-fluorescent semi-gloss specular components. In particualr, they represented fluorescence
as a diffuse reflection with a wavelength-shifting property,
i.e., a diffuse surface that reflects a different wavelength1.5

fluorescent emission
Lambertian cos

1.5

1

1

0.5

0.5

0

−60

-30

0
incident angles

30

60

0

diffuse reference
Lambertian cos

−60

-30

0
incident angles

30

60

Figure 3. Radiance changes due to different lighting directions:fluorescent emission (left) and diffuse surface (right)
Figure 2. Excitation and emission spectra of a fluorescent material

3.1. Bispectral Modelfrom the incident one. More recently, Hullin et al. proposeda more general and efficient way to model the appearanceof objects containing both non-fluorescent and fluorescentmaterials with bispectral bidirectional reflectance and reradiation distribution functions (BRRDF) [15]. Their method
resulted in a significant improvement in fluorescent object
models.
Regarding shape reconstruction, Hullin et al. introduced
a fluorescent immersion scanning system where an object
was embedded into a fluorescent liquid [14]. In this system,
light paths going through the fluorescent liquid become visible, and their incidence with the object’s surface can thenbe analyzed. Our approach is different in that it directly
uses the fluorescence from an object and it does not treat
fluorescent materials as a light transfer medium.

3. Bispectral Models for Reflectance and Reradiation
After decades of studies, fluorescence phenomena are
now able to be described with quantum theory [10, 24]: fluorescent materials always emit light at longer wavelengths
than the absorbed light and the emission spectra always
have the same frequency distribution (shape) regardless ofthe spectra of incident light. Namely, fluorescence showsa constant color (chromaticity) that is not affected by thecolor of the illumination [28].
The emissions of fluorescent materials are characterized
by their excitation and emission spectra. The excitation
spectra show how much energy from the illuminant is absorbed at each wavelength, and the emission spectra show
the spectral distribution of the emitted light from the fluorescent surfaces. Figure 2 shows the normalized excitationand emission spectra of one fluorescent material.1 The difference in wavelength between the positions of the maxima
of the excitation and emission spectra is known as Stokes
shift.
1 The spectral power distribution is normalized so that the minimum
intensity is 0 and the maximum intensity is 1.0.

To model the appearance of an object with ordinary reflective and fluorescent components, we need to consider
the transfer of energy from one wavelength to another. Recently, Hullin et al. devised a Bispectral Bidirectional Reflectance and Reradiation Distribution Function (bispectral
BRRDF) r(ω i , ω o , λi , λo ) that describes the angularly dependent reflectance for any pair of incoming and outgoingwavelengths [15]. In this function, ω i and ω o are the incident and reflection directions with respect to the surface
normal of the object, and λi and λo represent the incident
and outgoing wavelengths. The observed spectrum of a surface based on the bispectral BRRDF is
E(ω i , ω o , λi , λo ) = r(ω i , ω o , λi , λo )L(ω i , λi ) cos θi ,(1)
where L(ω i , λi ) is the illumination coming from the direction ω i at wavelength λi , and θi is the angle between thesurface normal and the light-source direction ω i .
Classic photometric stereo requires an object to have areflectance that is independent of the incident and outgoingdirections. One such example is an ideal diffuse surface
whose brightness can be described as
E(ω i , λ) = ρ(λ)L(ω i , λ) cos θi ,where λi = λo = λ and r(ω i , ω o , λi , λo ) in Equation 1 issimplified to the albedo of the object ρ(λ). It follows fromthis that, given the different directions of light with unit radiance at the wavelength λ, the brightness of a diffuse surface changes proportionally to cosθi . Classic photometricstereo makes use of this fact for estimating surface normals.
It is known that fluorescence has no directional character and is radiated uniformly in all directions [12]. A fluorescent emission behaves like it is from an ideal diffuse
surface except for the fact that it absorbs and re-emits lightat a different wavelength from the incident one [25]. Accordingly, it is found that the re-radiation property of fluorescence can be described by a directionally independentfunction µ(λi , λo ), and the emission from a fluorescent material illuminated by light L(ω i , λi ) can computed as
E(ω i , λi , λo ) = µ(λi , λo )L(ω i , λi ) cos θi .

(2)

Since fluorescent materials always emit light at longer
wavelength than that of the absorbed light, µ(λi , λo ) ' 0
for λi ≥ λo . Given fixed λi and λo for λi < λo , theobserved emission E(ω i , λi , λo ) becomes proportional tocosθi . We observed fluorescence from several objects under different lighting directions and verified that the brightness of the fluorescence (blue solid as shown in Figure 3left) could be well approximated by a Lambertian cosinelaw (red dotted line).We also verified that fluorescence isradiated uniformly in all directions, as described by Glassner [12]. It is known that the Lambertian model is sometimes not adequate to represent real-world rough surfaces
such as concrete, plaster, sand, and so on [23]. For reference, we measured the radiance changes in a white diffuse
reflectance target. We see a deviation from the Lambertianmodel that is due to surface roughness (Figure 3 right).
Let us go back to the original radiance equation and consider the appearance of a composite object containing bothordinary reflective and fluorescent components. Equation 1
can be rewritten as the sum of the brightnesses of the reflective and fluorescent components:
E(ω i , ω o , λi , λo ) = [f (ω i , ω o , λo )δ(λi − λo )+µ(λi , λo )]L(ω i , λi ) cos θi .

(3)Here, the reflective component (the first term) is characterized by a bidirectional reflectance distribution function
BRDF f (ω i , ω o , λo ). A delta function δ(λi − λo ) is
associated with it because an ordinary reflective component
reflects light at the same wavelength as λi . In other words,
we do not observe any brightness when λi 6= λo . From
Equation 3, we can see that some combinations of incident
and receiving wavelengths reveal certain properties about
the object.
Reflective component only: λi = λo . When the incident
and received light have the same wavelength, i.e. λi = λo ,almost no contribution from fluorescent component isobserved because µ(λi , λo ) ' 0 for λi ≥ λo . What we
observe is only the contribution from the non-fluorescentcomponent.
Fluorescent components only: λi < λo . When the wavelengths are different such that λi < λo , there is no contribution from the reflective component because δ(λi − λo ) = 0.
Therefore, only the emission from fluorescent component isseen.

4. Advantages of bispectral measurements forshape reconstruction
In the previous section, we saw that the wavelengthshifting properties of the fluorescence emission are usefulfor analyzing different properties of an object having

ordinary reflective and fluorescent component emissions.
In particular the ability to adjust the incident and observing
wavelengths provides the following advantages for shapereconstruction.

4.1. Specular free image
Specular reflection belongs to the reflective component
and is seen when the incident and outgoing wavelengths are
the same. In other words, we can avoid observing specularreflection by simply setting a different wavelength from theincident one as λo . Figure1 shows an example of specularfree images observed under near UV light in the red channelof a CCD camera.2 The object contains non-fluorescent andfluorescent components. Simply having the wavelengths sothat λi < λo provides an image of fluorescent component
only (Figure1 middle). This enables us to use specular-freeemission images for shape reconstruction. In this example, this object contains a few diffuse components, and thus,
the image obtained for λi = λo in the blue channel clearlyshows specular reflection (Figure1 right).

4.2. Less interreflection between fluorescent surfaces
For a concave object, interreflection between object surfaces often decreases the accuracy of the reconstructedshape. The wavelength-shifting property of fluorescent material lessens the influence of interreflection. In accordancewith the Stokes shift, a fluorescent material will not be excited much by its own emissions because there is not muchoverlap between its excitation and the emission spectra (Forinstance, see Figure 2). Accordingly, interreflections causedby fluorescence emissions are much less that those causedby diffuse reflections for scenes with a single material.
It should be noted that the emitted light from fluorescence materials have a chance of becoming secondary lightand being reflected by other surfaces. This happens only
when other surfaces have spectral reflectances within therange of its emission spectra. In our experiments, most objects consisted of a single material and contained different
colors of fluorescent and reflective components, and we did
not observe such phenomena. In the case of scenes withdifferent materials, however, the secondary light might bereflected by other surfaces. We will investigate the interaction between fluorescence and reflection in the future.

5. Bispectral Photometric Stereo
Photometric stereo estimates the surface normal of an
object by observing the object under different lighting conditions. Given irradiance E(ω k , λ) (k = 1, 2, . . . , K) at a
2 In Section 5.1 we describes the conditions to observe fluorescence using an ordinary color CCD camera and a light source.

point on a diffuse surface, we obtain a set of linear equationsof the formE(ω k , λ) = ρ(λ)L(ω k , λ) cos θk or
ek = ρn · lk ,where n is a surface normal of this point and lk is the direction of the kth light source. If the light-source directions
are known, we can recover ρn by using linear least squares.
Let us extend the classic photometric stereo approachto the case of bispectral measurements where the incident
and receiving wavelengths are different: λi 6= λo . As described in Section 3, when the received wavelength is longer(λi < λo ), we observe only the contribution from the fluorescence materials, whose appearance is described by Equation 2. Given a fixed λi and λo for λi < λo , the observed
emission E(ω k , λi , λo ) becomes proportional to the angle
between the surface normal and the light source direction
and has a form similar to that of the diffuse light:E(ωk , λi , λo ) = µ(λi , λo )L(ω k , λi ) cos θk or
ek = µn · lk ,from which we can recover µn by using least squares.
These equations are well-conditioned as long as the (threeor more) light source directions lk are linearly independent.

5.1. Observing emission-only images using RGB
camera and colored light source
In practice, it would be convenient if we could observe
the fluorescent component by using an ordinary color CCD
camera and a general light source. From Equation 3, theappearance of a composite object under illumination at all
wavelengths is
E(ω i , ω o , λi , λo ) = [f (ω i , ω o , λo )L(ω i , λo )Z+ µ(λi , λo )L(ω i , λi ) dλi ]cosθi .

(4)Here, the fluorescent component has the wavelengthshifting property, and thus, the overall observed spectrum
needs to be computed by summing up µ(λi , λo )L(ω i , λi )for all wavelengths λi . In contrast, only the reflection due
to the illumination at the wavelength λo , i.e. L(ω i , λo ),needs to be considered for the non-fluorescent component.
From Equation 4, we can see that the following conditions need to be satisfied to obtain emission-only images. First, the illuminant should have no energy at theoutgoing wavelength. i.e. L(ω i , λo ) = 0. This results in avoiding observing the reflective component. Secondly, the fluorescent material should absorb some energy
from the light and emit light in the wavelength λo :Rµ(λi , λo )L(ω i , λi ) dλi > 0.
Next, let us consider the case where the scene is observed
by a color camera. If we have a camera with three channels(R, G, and B), the brightness of a surface point of the object
for each channel isZ
Pq = cq (λo )[f (ω i , ω o , λo )L(ω i , λo )Z+ µ(λi , λo )L(ω i , λi ) dλi ] dλo cosθi ,(5)where cq (q = r, g, b) are the camera spectral sensitivities
for each channel. Similar to the previous case, the following conditions need to be satisfied to observe emission-only
images. For simplicity, let us consider the case where weobserve the scene in the red channel of the camera cr here.
First, the illuminant shouldhave no energy within theReffective range of cr . i.e. cr (λo )L(ω i , λo ) dλo = 0. If
there is no overlap between the illumination spectra and theeffective range of cr (λo ), the observed brightness in the redcolor channel does not have reflective components.3
Secondly, the fluorescent material should absorb someenergy fromR light andR emit light in the effective rangeof cr (λo ):cr (λo )[ µ(λi , λo )L(ω i , λi ) dλi ] dλo > 0.
Namely, the excitation spectra of the fluorescent material
needs to overlap with the illumination spectra, and its emission spectra needs to overlap with the effective range ofcr (λo ). In our experiments, we illuminated objects witha blue halogen lamp or LED UV light whose spectra do not
overlap with the effective range of the spectral sensitivities
for the green and red channels of a camera.

6. Results and Analysis
We tested our technique on images of real objects containing both fluorescent and reflective components. The objects used in our experiment naturally exhibit fluorescence
except the ceramic dish example. To obtain their emissiononly images, we illuminated objects with LED UV light (forceramic dish example) or a blue halogen lamp (for otherexamples) and captured object images in the red or green
channels of a CCD camera (SONY DXC-9000). For eachobject, 15 ∼ 30 images were captured with the object illuminated from different light source directions. The lightsource was about 1 m away from the object, which was
3 ∼ 8 cm in diameter.
We first evaluated the accuracy of our technique on a diffuse fluorescent sphere. Figure 4(a) (left) shows the appearance of the sphere under a white halogen lamp. Using UVlight, we checked that the color of its fluorescent component was green and its emission spectra fitted within therange of the color sensitivity in the green channel of thiscamera. The sphere also contained ordinary reflective components at longer wavelengths corresponding to red. This
allowed us to separately observe their contributions by using different combinations of light and color channels of the
3 More intuitively, this means that we do not observe any reflection in
the red channel under blue illumination.

(a) images of objects under natural lighting (for reference) and input imagesof objects under blue light.
(a) Images of object under white (for reference), blue light (for extracting fluorescence emission), and red light (for observing diffuse
reflection).

(b) Recovered shape for bridge-shaped and L-shaped objects.

(b) Shape recovered from reflection images.

Figure 5. Experimental results for concave objects.

from diffuse reflections and the ground-truth was 3.4
degrees. This shows that the photometric stereo approachbased on fluorescence emission performs better than thatbased on diffuse reflection in this experiment.

(c) Shape recovered from emission images.

Figure 4. Fluorescent diffuse sphere containing both fluorescentand reflective components.

camera. Images captured under blue light (Figure 4(a) middle) in the green channel show fluorescence only (emission
images), and images captured under red light (Figure 4(a)right) in the red channel show diffuse reflection (reflection
images).
Figures 4(b) and 4(c) show the estimated surface normals
and shapes of the sphere from reflection images and emission images respectively: the estimated surface normals are
stored directly in the RGB values of the surface normal map
images. The absolute values of the x, y, and z coordinates
are shown in red, green, and blue, respectively.4
Compared with the shape obtained from reflection
images based on photometric stereo (Figure 4(b)), we
can clearly see that our bispectral photometric stereo
method can estimate the surface normals and shape of theobject with equivalent accuracy (Figure 4(c)). The rootmean-square error between the surface normal directions
estimated from fluorescence emission and the ground-truth
was 2.0 degrees, and the error between those estimated
4 x and y axes correspond to the horizontal and vertical axis of the image plane, and the z axis is defined to be perpendicular to the image plane.

Concave Objects. We also tested our technique on concave
objects covered with different fluorescent materials. Figure5(a) shows the objects used in this experiment: a bridgeshaped wooden object painted fluorescent green and a Lshaped green fluorescent sheet. Figures 5(b) show the estimated shapes. In this figure, we can see that our method
could estimate their shapes regardless of their concavity.
This demonstrates the robustness of our method against interreflections between object surfaces. As described before,a fluorescent material will not be excited that much by its
own emission, and this property helps to make the estimatedshapes accurate even for concave objects.
Object with specular highlights . Our method is also effective on objects with specular reflection. The first test object was a key holder whose fluorescent component shows
green color. Figure 6(a) shows the appearance of this object
under blue light. We can see its fluorescent and reflective
components in the green and blue channels of this image.
In Figure 6(a) (right), the image of the reflective component
shows a significant amount of specular reflection, while thatof the fluorescent component (Figure 6(a) middle) is freefrom specularity. This enabled us to reliably estimate theshape of the object by applying photometric stereo to its
fluorescence images without suffering from specular reflection. The recovered shape is shown in Figures 6(b).
This object contained ordinary reflective components atlonger wavelengths corresponding to red. For comparison,
the shape of the object was estimated using images contain-

(a) Fluorescent component separated through bispectral measurement: image under near blue light (left), fluorescent-only image observed in the green channel (middle), and reflective-component-only
images observed in the blue channel of the camera (right).
(a) Image of a dish under white light and recovered shape from reflection.

(b) Image of a dish under UV light and recovered shape from fluorescence.

(b) Recovered shape from fluorescence.

(c) cross-sectional view of recovered
shape from fluorescence superimposed
into the side view of the dish.

Figure 7. Experimental results for a dish.

(c) Recovered shape from reflection.

Figure 6. Experimental results for a key holder.

ing reflective components captured under red light in red
channel. Compared with the recovered shape from reflective components (Figures 6(c)), we see that the fine details
such as letters and a key-shaped object were successfully
recovered by our method without suffering from specularreflection and interrefections (Figures 6(b)).
The second object was a ceramic dish composed of ordinary reflective components. This object had strong highlights spread all over its surface (Figure 7(a) left), and thismade it difficult to accurately recover its shape using photometric stereo approaches. For instance, if we directly apply
the classic photometric stereo to the images of this object,

the recovered shape is largely affected by its specular reflection (Figure 7(a) right).
To deal with a object with very sharp highlights, we canput special fluorescent paint on it. This paint is invisible under normal lighting, but it appears bright red under strong
UV light (Figure 7(b) left). In other words, we can add afluorescent component to a target object without changing
its appearance under normal lighting. In Figure 7(b) left,
we see that its non-fluorescent (especially specular reflection) and fluorescent components are separately observed in
the blue and red channels of the camera. Figure 7(b) rightshows the shape recovered from fluorescence images captured under UV light in the red channel: the cross-sectionalview of the recovered shape from fluorescence is superimposed into the side view of the object (Figure 7(c)). We
succeeded in obtaining an accurate shape without sufferingfrom specular reflection. This demonstrates the robustnessof our bispectral photometric stereo method against specular reflection.

7. Conclusion
We studied the appearance of fluorescence emissions under different lighting directions and presented a novel photometric stereo approach that made effective use of fluorescence in shape reconstruction. We showed that there is astrong similarity between fluorescence and ideal diffuse reflections and proposed to separate the fluorescence components from ordinary reflection components by using bispectral measurements. The unique wavelength-shifting property of fluorescence enables us to use emission-only images for shape reconstruction without suffering from specular reflection. This is the significant advantage of thefluorescence-based method over previous methods based onreflection. A future direction of this work would be to explore the use of fluorescence in other computer vision algorithms. There are many algorithms in computer visionthat assume Lambertian reflectance. We believe that fluorescence is very useful in the sense that it appears like anideal diffuse surface whose color is not affected by the colorof the illumination, and we can easily exclude specular reflection from the observation.

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