Selected Papers

Relief-like Depth Map Generation
Algorithm
Hajime Noto, Akihiko Hashimoto, Kazuo Kimura†,
and Kenji Nakazawa
Abstract
We propose a three-dimensional (3-D)-input method using a relief-like depth map generation algorithm (REAL). REAL is based on the concept of reproducing a depth map, like the relief of a coin, from
3-D input. It enables a portable 3-D-input system to be achieved using only a monocular camera and aphotoflash. REAL is very simple and convenient compared with conventional technology using triangulation. In this paper, we give an overview of the concept and the depth map calculations. Results of a subjective test conducted using 3-D images generated by REAL indicate that observers perceived natural 3D images.

1. Introduction
With the recent establishment of groups such as the
3-D Consortium [1] and the Consortium of 3-D
Image Business Promotion [2], the opportunities forusing three-dimensional (3-D) images are growing
rapidly. 3-D-output techniques include 3-D displays
based on parallax [3], [4] and lenticular [5] methods,
which have been developed commercially not only
for consumer products such as cellphones, but also
for personal computers (PCs) and amusement
machines [6]. In NTT Cyber Space Laboratories, weare researching and developing a DFD (depth-fused
3-D [7]) display that is less fatiguing to watch thanconventional stereoscopic displays. Before 3-D
images can find their way into consumer products, itwill be necessary to resolve not only software issues
such as the provision of attractive content, but also
hardware issues involved in making it just as easy to
input and output natural 3-D images as to take photographs with a camera.
Conventional 3-D-input technologies have mainly
been for industrial applications [8], where the main
requirements are accuracy and range for shape mea† NTT Cyber Space Laboratories
Musashino-shi, 180-8585 Japan
E-mail: kimura.k@lab.ntt.co.jp

Vol. 2 No. 8 Aug. 2004

surements. However, for consumer 3-D-input applications it is more important to concentrate on making
the equipment more compact, reducing the measurement times, and eliminating the need for a specialized
imaging environment—accuracy and range are not asimportant. Although various studies [9]-[13] havetackled these issues, they have yet to result in practical applications.
The light sectioning methods involve projecting
stripes of light onto the subject so as to scan it in a
number of light sections which are then imaged fromanother direction and converted into 3-D form by triangulation based on the direction from which thestripes were projected and the position from which
the subject is viewed. Triangulation methods involving the use of projected patterns (not just the lightsectioning methods) are characterized by their highaccuracy. On the other hand, to detect the projected
patterns correctly, it is generally necessary to use a
specialized imaging environment. Moreover, since
images are generally obtained one at a time whilechanging the projection angle of the stripe lightsource in order to scan the subject, the measurement
time is also long. Recently there have been reports[10], [11] of an ultrafast device that can perform measurements in real time, but this device requires a highintensity laser as the light source for the stripe lighting for adequate sensitivity.
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Stereo methods can be used to perform measurements based on the principle of triangulation fromimages taken by multiple cameras at different imaging positions. A characteristic of stereo methods isthat measurements (subject acquisition) can be performed in real time without the need for a special
imaging environment. However, since it is difficult toperform image processing to match up the same
objects from within natural images taken with multiple cameras, this method generally has poor accuracy
and reliability. Multi-baseline stereo methods [14]have been proposed as effective solutions for these
problems, and they have been employed in several
commercial stereo-method systems [15]-[17]. However, when configuring a multi-baseline stereo system it is necessary to increase the number of cameras
in proportion to the number of baselines, which isundesirable from the viewpoint of compactness.
A problem shared by all methods that use triangulation is that there are some regions whose depth cannot be obtained due to occlusion. Furthermore, since
the baseline must cover at least a certain length, they
are not suitable for portable systems. The relationshipbetween baseline length and imaging distance also
depends on the sensor resolution, but when measurements are performed with an imaging distance of 1–2
m, the baseline should normally be at least 5–10 cm
long. Since these issues affect size measurement
accuracy, they are difficult to solve in principle, so it
is difficult to apply measurement techniques based on
the principle of triangulation to consumer applications such as 3-D input for objects at size ranges comparable to human beings.
Conversion techniques that produce 3-D images
from 2-D images have also been studied [18], [19],but since these techniques do not use any information
derived from measurements, they are generally
unsuitable for obtaining solid images that are sufficiently natural.
This paper proposes a technique that adds pseudodepth information, which enables it to convey a perceptually natural 3-D impression when data obtainedby a rough 3-D-input method without the use of triangulation is depicted on a 3-D display. It enables aportable 3-D-input system to be achieved using onlya monocular camera and a photoflash. We give an
overview of the concept and the depth map calculations. Results of a subjective test conducted using 3D images added pseudo-depth indicate that observers
perceived natural 3-D images in a DFD display.

2. Concept
In this study we concentrated on objects such ascoins and medals with engraved relief patterns. As
shown in Fig. 1 [20], coins often have some kind ofdesign engraved in a relief pattern. These designs
cannot be made very thick, so they are engraved withrounded forms having more or less the same height,
but since human perception is based on previous
learning experience, humans can perceive a 3-D
impression that appears quite natural and varies with
the inclination and context of the design. If a coin
depicts the profile of a human face rendered withrelief gradations, with a building shown in the background, then the face can be perceived in 3-D without
any sense of incongruity. Thus, humans are able toperceive 3-D impressions even from thin relief
images engraved on walls or coins, without experiencing any particular feelings of incongruity.
We propose an algorithm for generating relief-like
depth maps as a new scheme based on the concept ofgenerating thin relief-type 3-D bodies by building up
a deformed pseudo-depth without considering theexact scale of the part to be modeled. This scheme iscalled REAL (relief-like depth map generation algorithm).
In REAL, an acquired image is made three-dimensional by adding relief-type distance data to it. To dothis it is necessary to decide which regions of theimage the relief depth information should be added
to. In this paper, as a typical example of a consumer
application, we assume that the algorithm is used toprocess pictures taken using a cellphone equippedwith a camera. Earlier studies have shown that the
subject is highly likely to be a human [21], [22] andthat a self-portrait of a female is the most common
subject [23]. This suggests that the main subject isoften situated quite close to the camera. Accordingly,
in the basic concept of REAL it is assumed that theparts that are to be made three-dimensional are in theFig. 1. Examples of relief on coins.

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Front

Side

Naturally lit image
CompareLighter parts are foreground.

Flash-lit image
Foreground
Step 1. Separate foreground from background.

Thresholding
Foreground

Binary image

Add generated
depth by applying
quadratic curve

Background

Depth map

Step 2. Add generated depth by applying quadratic curve.

Fig. 2. Schematic diagram of REAL.

foreground. Based on this assumption, the image isroughly separated into foreground and backgroundparts, and relief depth is added only to the foreground. Parts that are judged to be in the backgroundare all treated as background objects regardless of
their true distance. Figure 2 summarizes this process.
2.1 Processing of REAL
A step-by-step description of REAL is presented
below.
• Step 1: Separate foreground and background
First, the foreground and background are separated
in order to extract the region to which the relief processing is to be applied. The difference in image
intensities between a naturally lit image and a flashlit image of the subject is evaluated and comparedwith a fixed threshold to obtain a binary image. The
threshold value used during this differencing process
is affected by numerous factors including the ambient
light, the flash intensity, the distance to the subject,
the reflectivity of the subject, and the signal-to-noise
ratio of the camera. However, to simplify the computation in this procedure, a single preset threshold isused in this process.
Vol. 2 No. 8 Aug. 2004

• Step 2: Add relief tone pseudo-depth to the object
In REAL, the smallest depth is applied to the central region of the objects judged to be in the foreground, while their perimeter lines are given depths
that connect smoothly with the background from thecenter of the object. Since the REAL depths are considered relative to the viewer, the smallest depth is set
to a distance of zero (i.e., no depth). The reason thesmallest depth is applied within a fixed range of thecenter region is to accentuate the jumping-out feeling.
Specifically, the algorithm determines the centroidof each extracted object and uses quadratic curves as
expressed by Eq. (1) to represent the change in depth
from the centroid to the perimeter.
02f ( x ) =   x / l − r0 L  1 − r0 

(0 ≤ x ≤ r0 ⋅ l )(r0 ⋅ l < x ≤ l )(1)Here, L is the depth of the background (L≥0), l isthe distance from the centroid to the perimeter (l≥0),
r0 is the ratio of the object allocated to the smallest
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depth range (0≤r0≤1), and x is the distance from thecentroid (0≤x≤l).
Figure 3 shows the pseudo-depth added to the binary image. Here, f(x) represents the 3-D variation of
the depth map, where the protruding regions areshown in lighter shades. Since the regions withgreater protrusion are closer to the viewer, the positions in the image with the maximum intensity value
have the smallest depth. Taking the distance l fromthe centroid to the perimeter to be 100%, the object is
assigned to the smallest depth from the viewer
Near

CentroidlFar(f(x)=0) for a distance determined by r0 from the centroid (here, 30% of the distance l). Beyond the distance determined by r0, pseudo-distance is added byapplying a quadratic curve so that the distance at theperimeter of the extracted object matches the lengthof the background. Pseudo-depth is thereby added by
performing the abovementioned process for every
point on the perimeter.
In REAL it is defined that relief tones must varysmoothly without any sharp changes, but in the
results of step 2 there are some parts where the depth
is not smooth inside the object due to differences inthe distance from the centroid to the perimeter. To
remove these sharp depth changes, the depth map issubjected to a smoothing process. In this paper as thefilter size we use a relatively large size of at least
0.05% of the image area. This value was obtained byexperience from the results of viewing with a DFD
display as the size at which a natural 3-D image canbe perceived.
3. Comparison of depth generated by REAL withactual depth

Perimeter
30% = r0

Depth

Lf (x )
0

100%
x /l

Fig. 3. Adding generated depth by applying quadratic
curve.

SphereFigure 4 compares the depth generated by REAL
with the actual depth in typical 3-D images. In REAL
the results are close to the actual depth if the depth
profile of the subject is spherical, but stray from theactual profile otherwise. For example, in the case of acylinder the actual depth is only rounded in the horizontal direction, but in REAL, rounding is applied inall directions from the centroid. Also, in the case of
two adjacent spheres the actual depth is indented in
the central region, whereas in REAL the central
region sticks out. Even in cases where the depth proCylinder

Two spheres

Box

Actual depth map

REAL depth map

Examples ofactual images withsimilar shapes

Fig. 4. Depth map comparison of REAL with actual 3-D data.

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file is flat, as with a box shape, the results produced
by REAL are still rounded in all directions. However,with this degree of discrepancy, when the context ofthe foreground and background is correct and thedepth is continuous and smooth, it is possible to perceive a 3-D impression without any feeling of incongruity by pasting a texture onto this 3-D profile.

it assigns a depth to every pixel in the image(albeit a pseudo-depth), it does not suffer fromthe occlusion problems that have plagued conventional techniques using triangulation.
(e) Natural 3-D impression
By pasting a texture onto the pseudo-depth of
the relief tones, it is possible to obtain a perceptually natural 3-D impression.

4. Characteristics of REAL
5. Subjective evaluation tests
The characteristics of REAL are discussed below.
(a) Compact and low cost
The foreground/background separation is a
type of distance measurement, but since only
rough judgments are made it can be implemented
with just a camera and a flash. It is thus easy tomake the device compact. Since ordinary compact cameras and flash bulbs perform adequately
for this purpose, the equipment can be implemented much more cheaply than conventional 3D-input devices.
(b) Simple computational processing
REAL uses only simple image processing techniques such as image differencing, thresholding,and quadratic depth interpolation, so it can be
fully implemented in real time on commercial
PCs. We expect that in the near future even thecentral processing units (CPUs) incorporated into
mobile equipment such as cellphones and personal digital assistants (PDAs) will be able to perform this processing in real time.
(c) Natural image input
REAL can basically operate up to ranges where
the light from a flashbulb produces a difference inbrightness. Unlike the light sectioning method it
does not require a special imaging environment.
(d) Acquisition of texture and depth data with amonocular device
With REAL, a monocular device can acquire
texture data and depth data simultaneously. Since

We conducted subjective evaluation tests to examine whether the depth of the relief tones generated by
REAL conveys a natural impression to the viewer
when presented on a 3-D display.
5.1 Experiments
In the experiments, the test subjects were shown areference image and a comparative image simultaneously for 15 seconds and were then asked to evaluate
the comparative image relative to the reference image
on a scale of five levels (very good, good, same, poor,
very poor). A blank display period of 5 seconds wasinserted before the presentation of the next image pair
to prevent the results being affected by the previous
evaluation. To make the test subjects aware of therange of fluctuation of 3-D impression, after one
practice run, two evaluation runs were performed
under the same conditions with the evaluation images
presented in random order. A total of nine test subjects were used. An example of the image presentation sequence is shown in Fig. 5.
Figure 6 illustrates how the images were presented
on the DFD display device in the experiments, andFig. 7 shows the images used in the evaluation, whichwere the typical images shown in Fig. 4. For each
evaluation image we prepared a REAL image, a
backdrop image, and a planar (2-D) image, whichwere displayed as shown in Fig. 6. As comparative
images we prepared REAL images and backdrop

Reference
image
1–1

Reference
image
1–2

Comparative
image

Comparative
image

Sequence number

Evaluation images

Sequence number

Evaluation images

5 seconds

15 seconds

5 seconds

15 seconds

Fig. 5. Evaluation procedure for subjective test.

Vol. 2 No. 8 Aug. 200445

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Rear

Rear

Front

Rear

Front

Front

(a) REAL(b) Backdrop(c) Planar

Depth-fused 3-D images
generated using REAL depth
map are displayed in front andrear screens.

The foreground objects are displayed in
the front screen. The backgroundobjects are displayed in the rear screen
like a stage backdrop.

A 2-D image is displayed in the rear
screen alone. The front screen istransparent.

Fig. 6. Types of evaluation images used in subjective test.

Evaluation image 1

Evaluation image 2

Evaluation image 3

Evaluation image 4

Fig. 7. Evaluation images used in the subjective test.

images. The REAL images were 3-D images generated using a REAL depth map. The backdrop images
were images in which the foreground object was cut
out and displayed in planar form by positioning it infront of its background, which acted like a stage
backdrop in a theater. The subjective evaluation
experiments were performed by judging criteria infour categories using the planar images as reference
images. The evaluated criteria were as follows:(1) 3-D impression
Does the foreground of the evaluation image
stand out compared with the reference image?
(2) Natural impression
Does the evaluation image appear natural compared with the reference image?
(3) Image quality
Does the evaluation image look good comparedwith the reference image?
(4) Overall
Does the evaluation image seem better than thereference image?
A DFD display device was used for the 3-D display.
Figure 8 shows the setup used in the subjective evaluation tests. The REAL, backdrop, and planar images
were scaled to a size of 2 inches and presented at aviewing distance of 300 mm. The image size and46

Rear LCD

3.0 mmImage offront LCD
Half mirror

300 mmFront LCD

Display size: 2 inches
Resolution: QVGA (320 × 240)

Test subject

Fig. 8. Setup of subjective test using a depth-fused 3-D
display.

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viewing distance were chosen to correspond to cellphone usage. The depth representation range of the 3D display was 3.0 mm.
5.2 Experimental results
Figure 9 shows the results of analyzing the evaluation scores recorded for each of the evaluation criteria. The evaluation scores provided by each test subject were averaged together for each evaluation image
when presented as a REAL image, a backdrop image,and a planar image.
Before examining the results relating to each evaluation criterion, we will describe the tendencies of
the test subjects. The white circles in Figs. 9(a)–(d)are the theoretical values for the planar images. Since
the reference images and planar images were identical, the same evaluation results should in theory be
selected for both. However, test subject 4 evaluatedthis image as “very poor” in one instance. Also, there
were many cases in which test subject 9 evaluated this
Very good

REAL

image as “good” or even “very good”. A closer lookat the evaluation results provided by test subject 4
reveals that this test subject tended to give lower
scores than the other test subjects for nearly all theitems regardless of whether or not they were presented in planar form. Similarly, test subject 9 tended
toward higher scores than the other test subjects. Thisis assumed to be because different offsets wereapplied to the evaluation standard by different test
subjects even when the same reference values wereshown. However, the tendencies in the evaluation ofeach comparative image (the relative relationship ofthe evaluation scores) were more or less consistent,
so we think that these results can be analyzed byobtaining the average value in this rating scale
method.
We examined how the REAL images were perceived by the viewers compared with the conventional image (planar image) for each evaluation criterion.
The difference between the scores was confirmed
REAL

REAL is better than 2-D.
AverageGood

Test subject 1
REAL is similar to 2-D.

Same

Test subject 2
Test subject 3

Poor

Test subject 4
Test subject 5

Very poor

Test subject 6
Test subject 7
Test subject 8
Test subject 9

Backdrop

2-D(a) Results for 3-D impression

Backdrop

2-D(b) Results for natural impression

REAL

REAL
REAL is similar to 2-D.

REAL is the best.

Backdrop

2-D(c) Results for image quality

Backdrop

2-D(d) Overall results

Fig. 9. Results of subjective test.

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with a 1% significant difference by performing at-test*.
In the subjective evaluation results for “3-D impression”, the REAL and backdrop images scored better
than the planar images. This shows that even with adepth of about 3.0 mm it is possible to perceive a 3-D
impression. There was no difference between the
REAL images and backdrop images in terms of their
3-D impression.
In the subjective evaluation results for “naturalimpression”, the planar and REAL images obtained
similar scores, while the backdrop images obtained
lower scores. This shows that it is possible to perceivea natural 3-D impression similar to that of planar
images if pseudo-depth is added in the form of relief
tones to only the foreground parts of the image.
In the subjective evaluation results for “image quality”, the planar and REAL images obtained similarscores, while the backdrop images obtained lower
scores. Since all the images had the same resolution,
we infer that this difference was due to the gaps thatappeared in the background of backdrop images dueto the cutting away of the foreground parts, thereby
causing a reduction in the image quality perceived by
the viewers.
In the “overall” subjective evaluation results, the
REAL images scored higher than the planar images,
while the backdrop images scored lower. The overall
evaluation was an evaluation of the viewer’s overall
preferences related to the images, and this shows that
the REAL images were rated as well as or better thanordinary planar images.
6. Conclusion
We proposed a three-dimensional-input method
using a relief-like depth map generation algorithm(REAL). REAL is based on the concept of reproducing a depth map, like the relief of a coin, from 3-D
input. It enables a portable 3-D-input system to beachieved using only a monocular camera and aphotoflash. REAL is very simple and convenientcompared with conventional technology using triangulation. We also gave an overview of the concept
and the depth map calculations. Results of a subjective test conducted using 3-D images generated by
REAL indicate that observers perceived natural 3-D
images on DFD displays. Our experimental results* t-test: The two-sample t-test is used to determine the difference
between the average values of two groups. The meaning of 1%
significant difference is that the error of the t-test is 1%.

48

suggest that using REAL for 3-D-input applications
in consumer applications will lead to devices that are
more compact and have shorter measurement times
and less stringent environmental operating criteria,
allowing 3-D input to be achieved without accurate
distance measurements.
References[1][2]“3D Consortium,” http://www.3dc.gr.jp/english/index.html
T. Honda, “About the activity of ‘Consortium of 3-D Image Business
Promotion’,” 3D Image Conference 2003, Tokyo, Japan, pp. 205-207,
July 2003 (in Japanese).
[3] T. Ando, K. Mashitani, T. Takemoto, M. Higashino, G. Hamagishi,
and T. Kobayashi, “A multi-view 3-D display without special glasses,” Technical report of IEICE, EID2002-45, pp. 33-36, 2002 (inJapanese).
[4] J. Harrold, A. M. S. Jacobs, G. J. Woodgate, and D. Ezra, “3D Display Systems Hardware Research at Sharp Laboratories of Europe: anupdate,” Sharp Technical Journal, No. 74, pp. 24-30, 1999.
[5] A. Miyazawa, “3D imaging technologies for computer-based gamemachines,” Technical report of IEICE, EID2002-49, pp. 49-52, 2002
(in Japanese).
[6] T. Kotani, “Aiming at pachinko machines and cellphones using 3D
displays with semicylindrical lenses with no loss of intensity,” Nikkei
Electronics, Jan. 6, 2003, pp. 26-27, 2003 (in Japanese).
[7] S. Suyama, H. Takada, K. Uehira, S. Sakai, and S. Ohtsuka, “A New
Method for Protruding Apparent 3-D Images in the DFD (DepthFused 3-D) Display,” SID 01 Digest, 54.1, pp. 1300-1303, 2001.
[8] “Special Feature: 3D Data Sensing Technology,” O plus E 20, 11, pp.
1251-1280, 1998 (in Japanese).
[9] K. Sato, “Range sensors,” ITE Journal 54, 2, pp. 157-159, 2000 (inJapanese).
[10] S. Yoshimura, T. Sugiyama, K. Yonemoto, and K. Ueda, “A 48
Kframe/s CMOS Image Sensor for Real-time 3-D Sensing andMotion Detection,” ISSCC 2001 Digest of Technical Papers, San
Francisco, California, U. S. A., pp. 94-95, Feb. 2001.
[11] T. Sugiyama, S. Yoshimura, R. Suzuki, and H. Sumi, “A CMOS sensor capable of color video imaging and real-time 3D measurements,”
ITE Technical Report 26, 26, pp. 1-16, 2002 (in Japanese).
[12] Y. Yamaguchi, K. Tokai, and T. Iyoda, “Feasibility investigation ofmobile 3D image input system based on spatial re-encoding method,”
Proceedings of the 2001 Information and Systems Society Conferenceof IEICE, D-11-67, p. 152, 2001 (in Japanese).
[13] H. Noto and T. Okimura, “Study of 3D-information measurement
method using spatial codes,” Proceedings of the 2001 Information and
Systems Society Conference of IEICE, D-11-68, p. 153, 2001 (inJapanese).
[14] M. Okutomi and T. Kanade, “A multiple-baseline stereo,” IEEE
Trans. Pattern Anal. & Mach. Intell. 15, 4, pp. 353-363, 1993.
[15] S. Kimura, T. Shinpo, E. Kawamura, H. Yamaguchi, and K. Nakano,“A new real-time stereoscopic processing device using spatial filtering,” IEICE PRMU97-207, pp. 1-8, 1998 (in Japanese).
[16] S. Kuwashima, “Color Triclops: The world’s first PC-based full-color
stereoscopic vision systems,” Eizojoho Industrial 31, 4, pp. 17-22,
1999 (in Japanese).
[17] S. Shimizu, K. Yamamoto, C. Wang, Y. Sato, H. Tanahashi, and Y.
Niwa, “Detection of moving object from mobile stereo omni-directional system (SOS),” Proceedings of 9th Symposium on Sensing via
Image Information, Yokohama, Kanagawa , Japan, pp. 531-536, Sep.
2003 (in Japanese).
[18] H. Murata, “Synthesizing techniques of 3D image; 2D-to-3D image
conversion technology,” ITE Journal 54, 3, pp. 332-337, 2000 (inJapanese).
[19] “Sharp Corporation SH251iS,” http://www.sharp.co.jp/products/
sh251is/ (in Japanese)

NTT Technical Review

Selected Papers[20] “Moneymuseum,” http://www.geldauktion.ch/index_english.html[21] “Kikasete.net questionnaire on camera-equipped cellphones,”
http://www.kikasete.net/marketer/mk_tw62.php (in Japanese)[22] H. Eda, “Hit products for the consumer age: Catering for the selfrespecting consumer,” Nikkei Electronics, Jan. 20, 2003, pp. 59-66,
2003 (in Japanese).
[23] “Commentary: Selection or coexistence? Cellphones vs. digital cameras. Part 1 — User trends: Nikkei BP Consulting Edition, Development centered on non-technical users,” Nikkei Mechanical, Sep. 2003
No. 588, pp. 42-43, 2003 (in Japanese).

Hajime Noto
Visual Media Communications Project, NTT
Cyber Space Laboratories.
He received the B.E. and M.E. degrees in management engineering from Kansai University,
Osaka in 1997 and 1999, respectively. In 1999,
he joined NTT Cyber Space Laboratories,
Tokyo, where he is engaged in R&D of 3-Dinput/output techniques. He is a member of theInstitute of Image Information and Television
Engineers of Japan (ITE).

Akihiko Hashimoto
Senior Manager, Solution Business Division,
NTT Communications.
He received the B.E. and M.E. degrees in electronics engineering from Tokyo Institute ofTechnology, Tokyo in 1983 and 1985, respectively. In 1985, he joined NTT Human Interface
Laboratories, Yokosuka, where he was engaged
in research on computer graphics and computer
vision systems. He was also engaged in researchon 3-D-input systems in NTT Communication
Science Laboratories and NTT Cyber Space Laboratories. He is currently working on the IC business for NTT Communications. He is a memberof ITE.

Kazuo Kimura
Senior Research Engineer, Visual Media Communications Project, NTT Cyber Space Laboratories.
He received the B.E. and M.E. degrees in electronics engineering from Niigata University,
Niigata in 1982 and 1984, respectively. In 1984,
he joined NTT Electrical Communications Laboratories, Tokyo, where he worked on activematrix liquid-crystal displays. Later, he wasengaged in the development of Internet facsimile systems and their operation systems in NTT
Communications. He is currently engaged in
R&D of high-reality systems using 3-D display
and image systems. He is a member of ITE.

Kenji Nakazawa
Senior Research Engineer, Visual Media Communications Project, NTT Cyber Space Laboratories.
He received the B.E. and M.E. degrees in electronics in 1981 and 1983, respectively, and the
Ph.D. degree in materials science and engineering in 1991, all from Kanazawa University,
Ishikawa. He joined NTT Electrical Communications Laboratories, Tokyo in 1983 and wasengaged in research on amorphous and polycrystalline Si thin-film materials and TFTs using
these films. He was also engaged in R&D oflarge-screen-size super-high-resolution display
systems. He is currently engaged in R&D of 3-D
display and image systems. He is a member of
the Institute of Electronics, Information andCommunication Engineers, ITE, and the Society
for Information Display.

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