• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1334-1337
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• 2009

The human vision system has visual functions for viewing 3D images with a correct depth. These functions are called accommodation, vergence and binocular stereopsis. Most 3D display system utilizes binocular stereopsis. The authors have developed a monocular 3D vision system with accommodation mechanism, which is useful function for perceiving depth.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.171-174
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• 2003

In this paper, we propose the method of stereo images composition using adaptive dense disparity estimation. For the correct composition of stereo image and 3D virtual object, we need correct marker position and depth information. The existing algorithms use position information of markers in stereo images for calculating depth of calibration object. But this depth information may be wrong in case of inaccurate marker tracking. Moreover in occlusion region, we can't know depth of 3D object, so we can't composite stereo images and 3D virtual object. In these reasons, the proposed algorithm uses adaptive dense disparity estimation for calculation of depth. The adaptive dense disparity estimation is the algorithm that use pixel-based disparity estimation and the search range is limited around calibration object.

• Journal of Information Display
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• v.10 no.1
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• pp.1-5
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• 2009

A novel computational integral imaging technique with enhanced depth sensitivity is proposed. For each lateral position at a given depth plane, the dissimilarity between corresponding pixels of the elemental images is measured and used as a suppressing factor for that position. The intensity values are aggregated to determine the correct depth plane of each plane object. The experimental and simulation results show that the reconstructed depth image on the incorrect depth plane is effectively suppressed, and that the depth image on the correct depth plane is reconstructed clearly without any noise. The correct depth plane is also exactly determined.

• Korean Journal of Optics and Photonics
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• v.18 no.4
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• pp.246-255
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• 2007

The floating image system (FIS) is a device to display input source in the space between fast surface of the display and an observer and it provides pseudo 3D depth to an observer when input source as real object or 2D image was displayed through the optical lens system in the FIS. The Advanced floating image system (AFIS) was designed to give more effective 3D depth than existing FIS by adding front and rear depth cues to the displayed stereogram, which it was used as input source. The magnitude of disparity and size of stereogram were strongly related each other and they have been optimized for presenting 3D depths in a non-optical lens systems. Thus, if they were used in optical lens system, they will have reduced or magnified parameters, leading to problem such as providing incorrect 3D depth cues to an observer. Although the size of stereogram and disparity were demagnified by total magnifying power of optical system, the viewing distance (VD) from the display to an observer and base distance (BD) for the gap between the eyes were fixed. For this reason, the quantity of disparity in displayed stereogram through the existing FIS has not kept the magnifying power to the total optical system. Therefore, we proposed the methods to provide correct 3D depth to an observer by compensating quantity of disparity in stereogram which was satisfied to keep total magnifying power of optical lenses system by AFIS. Consequently, the AFIS provides a good floating depth (pseudo 3D) with correct front and rear 3D depth cues to an observer.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08b
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• pp.1490-1493
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• 2007

We proposed the method to take 3D image having correct depths to the front and rear directions when the stereogram was displayed to an observer through an optical system. Since the magnified stereogram by lenses was not given correct depth to an observer despite having the same magnified disparity. Consequently, we achieved our goal by relations of compensated disparities to both directions with magnification of lenses, viewing distance and base distance of viewer in AFIS.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.745-752
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• 2016

We suggest an efficient Simultaneous Localization and 3D Polygon Map Building (SLAM) method with Kinect depth sensor for mobile robots in indoor environments. In this method, Kinect depth data is separated into row planes so that scan line segments are on each row plane. After grouping all scan line segments from all row planes into line groups, a set of 3D Scan polygons are fitted from each line group. A map matching algorithm then figures out pairs of scan polygons and existing map polygons in 3D, and localization is performed to record correct pose of the mobile robot. For 3D map-building, each 3D map polygon is created or updated by merging each matched 3D scan polygon, which considers scan and map edges efficiently. The validity of the proposed 3D SLAM algorithm is revealed via experiments.

• Journal of the Korea Computer Industry Society
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• v.9 no.3
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• pp.105-114
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• 2008

We present an eye tracking system using a low cost 3D CMOS imager for 3D displays that ensures a correct auto stereoscopic view of position- dependent stereoscopic 3D images. The tracker is capable of segmenting the foreground objects (viewer) from background objects using their relative distance from the camera. The tracker is a novel 3D CMOS Image Sensor based on Time of Flight (TOF) principle using innovating photon gating techniques. The basic feature incorporates real time depth imaging by capturing the shape of a light-pulse front as it is reflected from a three dimensional object. The basic architecture and main building blocks of a real time depth CMOS pixel are described. For this application, we use a stereoscopic type of display using parallax barrier elements that is described as well.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.707-709
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• 2008

We proposed the method to present corrected depth cue to an observer by stereoscopic display. It was performed in sequence that designing the displayed space having a constant interval of depth and then defining the object space which had considered to an environment of display and based on computer graphics. Consequently, we had performed a different process of reported existing methods distinctively and taken the result which correctly designed depth cue having linearity whatever various sizes of display would be used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4968-4986
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• 2017

In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.6
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• pp.1431-1438
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• 1995

In this paper, we present a multiple-view stereo matching method in case of moving in the direction of optical axis with stereo camera. Also we analyze the obtainable depth precision to show that multiple-view stereo increases the virtual baseline with single-view stereo. This method decides candidate points for correspondence in each image pair and then search for the correct combinations of correspondences among them using the geometrical consistency they must satisfy. Adantages of this method are capability in increasing the accuracy in matching by using the multiple stereo images and less computation due to local processing. This method computes 3-D depth by averaging the depth obtained in each multiple-view stereo. We show that the resulting depth has more precision than depth obtainable by each independent stereo when the position of image feature is uncertain due to image noise. This paper first defines a multipleview stereo agorithm in case of moving in the direction of optical axis with stereo camera and analyze the obtainable precision of computed depth. Then we represent the effect of removing the incorrect matching candidate and precision enhancement with experimental result.