• Cartoon and Animation Studies
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• s.37
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• pp.221-245
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• 2014

With the success of the world's first 3D computer animated film, "Toy Story" in 1995, industrial development of 3D computer animation gained considerable momentum. Consequently, various 3D animations for TV were produced; in addition, high quality 3D computer animation games became common. To save a large amount of 3D animation production time and cost, technological development has been conducted actively, in accordance with the expansion of industrial demand in this field. Further, compared with the traditional approach of producing animations through hand-drawings, the efficiency of producing 3D computer animations is infinitely greater. In this study, an experiment and a comparative analysis of markerless motion capture systems for facial expression animation has been conducted that aims to improve the efficiency of 3D computer animation production. Faceware system, which is a product of Image Metrics, provides sophisticated production tools despite the complexity of motion capture recognition and application process. Faceshift system, which is a product of same-named Faceshift, though relatively less sophisticated, provides applications for rapid real-time motion recognition. It is hoped that the results of the comparative analysis presented in this paper become baseline data for selecting the appropriate motion capture and key frame animation method for the most efficient production of facial expression animation in accordance with production time and cost, and the degree of sophistication and media in use, when creating animation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.3
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• pp.8-14
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• 2012

Improving the speed of image processing is in great demand according to spread of high quality visual media or massive image applications such as 3D TV or movies, AR(Augmented reality). SIMD computer attached to a host computer can accelerate various image processing and massive data operations. MAMS is a multi-access memory system which is, along with multiple processing elements(PEs), adequate for establishing a high performance pipelined SIMD machine. MAMS supports simultaneous access to pq data elements within a horizontal, a vertical, or a block subarray with a constant interval in an arbitrary position in an $M{\times}N$ array of data elements, where the number of memory modules(MMs), m, is a prime number greater than pq. MAMS-PP4 is the first realization of the MAMS architecture, which consists of four PEs in a single chip and five MMs. This paper presents implementation of image processing algorithms and performance analysis for MAMS-PP16 which consists of 16 PEs with 17 MMs in an extension or the prior work, MAMS-PP4. The newly designed MAMS-PP16 has a 64 bit instruction format and application specific instruction set. The author develops a simulator of the MAMS-PP16 system, which implemented algorithms can be executed on. Performance analysis has done with this simulator executing implemented algorithms of processing images. The result of performance analysis verifies consistent response of MAMS-PP16 through the pyramid operation in image processing algorithms comparing with a Pentium-based serial processor. Executing the pyramid operation in MAMS-PP16 results in consistent response of processing time while randomly response time in a serial processor.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.4
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• pp.267-273
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• 2005

Stereo image analysis has been an important tool for reconstructing 3D terrain. By In its nature, occlusion is one of difficulties Ive cannot avoid in stereo matching. This paper presents a study on occlusion detection by employing LRC(Left-Right Check) and OCC(Occlusion Constraint) and how we can improve the accuracy of DEM(Digital Elevation Model) y using interpolated data into the detected occluded area. Experimental results show that these method can effectively detect occluded regions and improve the accuarcy of DEM using the occlusion detection.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.71-78
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• 2021

In order to classify a target image in a cluster of images, the difference in brightness between the object and the background is mainly concerned, which is not easy to classify if the shape of the object is blurred and the sharpness is low. However, there are a few studies attempted to solve these problems, and there is still the problem of not properly distinguishing between wrong pattern and right pattern images when applied to actual data analysis. In this paper, we propose an algorithm that classifies 3D films into sharp and blurry using the width of the pixel values histogram. This algorithm determines the width of the right and wrong images based on the width of the pixel distributions. The larger the width histogram, the sharp the image, while the shorter the width histogram the blurry the image. Experiments show that the proposed algorithm reflects that the characteristics of these histograms allows classification of all wrong images and right images. To determine the reliability and validity of the proposed algorithm, we compare the results with the other obtained from preprocessed 3D films. We then trained the 3D films using few-shot learning algorithm for accurate classification. The experiments verify that the proposed algorithm can perform higher without complicated computations.

• Progress in Medical Physics
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• v.17 no.2
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• pp.67-76
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• 2006

We evaluated the accuracy of a patient setup error correction due to reference image quality for a 2D-2D matching process. Digitally reconstructed radiographs (DRRs) generated by use of the Pinnacle3 and the Eclipse for various regions of a humanoid phantom and a patient for different CT slice thickness were employed as a reference images and kV X-ray Images from the On-Board Imager were registered to the reference DRRs. In comparison of the DRRs and profiles, DRR image quality was getting worse with an increase of CT image slice thickness. However there were only slight differences of setup errors evaluation between matching results for good and poor reference DRRs. Although DRR image quality did not strongly affect to the 2D-2D matching accuracy, there are still potential errors for matching procedure, therefore we recommend that DRR images are needed to be generated with less than 3mm slice thickness for 2D-2D matching.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.1
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• pp.39-43
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• 2012

Purpose: In hospital image-guided radiation therapy in patients with bladder cancer to enhance the reproducibility of the appropriate amount, depending on the patient's condition, and image-guided injection of saline system (On-Board Imager system, OBI, VARIAN, USA) three of the Cone-Beam CT dimensional matching (3D-3D matching) to be the treatment. In this study, the treatment of patients with bladder cancer at Cone-Beam CT image obtained through the analysis of the bones based matching and matching based on the bladder to learn about the differences, the bladder's volume change injected saline solution by looking at the bladder for the treatment of patients with a more appropriate image matching is to assess how the discussion. Materials and Methods: At our hospital from January 2009 to April 2010 admitted for radiation therapy patients, 7 patients with bladder cancer using a Folly catheter of residual urine in the bladder after removing the amount determined according to individual patient enough to inject saline CT-Sim was designed after the treatment plan. After that, using OBI before treatment to confirm position with Cone-Beam CT scan was physician in charge of matching was performed in all patients. CBCT images using a total of 45 bones, bladder, based on image matching and image matching based on the difference were analyzed. In addition, changes in bladder volume of Eclipse (version 8.0, VARIAN, USA) persuaded through. Results: Bones, one based image matching based on the bladder and re-matching the X axis is the difference between the average $3{\pm}2mm$, Y axis, $1.8{\pm}1.3mm$, Z-axis travel distance is $2.3{\pm}1.7mm$ and the overall $4.8{\pm}2.0mm$, respectively. The volume of the bladder compared to the baseline showed a difference of $4.03{\pm}3.97%$. Conclusion: Anatomical location and nature of the bladder due to internal movement of the bones, even after matching with the image of the bladder occurred in different locations. In addition, the volume of saline-filled bladder showed up the difference between the 4.03 percent, but matched in both images to be included in the planned volumes were able to confirm. Thus, after injection of saline into the bladder base by providing a more accurate image matching will be able to conduct therapy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.207-209
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• 2017

3D printing, will make it integrated into one of the important branches of animation art, such as stop-motion Animation, to improve stop-motion Animation and put the modern science and technology and the manual craft into perfect combination. Throughout the development of stop-motion Animation, innovation in traditional concept is needed, to put the 3D printing integrated into traditional making and apply it to stop-motion Animation creation, and make sure to reconsider the animation production technology and production material, exploit its unique and distinctive features in multi-level and multi-angle, reshape art form of stop-motion Animation so as to highlight the advantages of 3D printing in making stop-motion animation.

• The korean journal of orthodontics
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• v.36 no.1 s.114
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• pp.1-13
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• 2006

Three-dimensional (3-D) laser scans can provide a 3-D image of the face and it is efficient in examining specific structures of the craniofacial soft tissues. Due to the increasing concerns with the soft tissues and expansion of the treatment range, a need for 3-D soft tissue analysis has become urgent. Therefore, the purpose of this study was to evaluate the scanning error of the Vivid 900 (Minolta, Tokyo, Japan) 3-D laser scanner and Rapidform program (Inus Technology Inc., Seoul, Korea) and to evaluate the mean error and the magnification percentage of the image obtained from 3-D laser scans. In addition, soft tissue landmarks that are easy to designate and reproduce in 3-D images of normal, Class II and Class III malocclusion patients were obtained. The conclusions are as follows; scanning errors of the Vivid 900 3-D laser scanner using a manikin were 0.16 mm in the X axis, 0.15 mm in the Y axis, and 0.15 mm in the Z axis. In the comparison of actual measurements from the manikin and the 3-D image obtained from the Rapidform program, the mean error was 0.37 mm and the magnification was 0.66%. Except for the right soft tissue gonion from the 3-D image, errors of all soft tissue landmarks were within 2.0 mm. Glabella, soft tissue nasion, endocanthion, exocanthion, pronasale, subnasale, nasal alare, upper lip point, cheilion, lower lip point, soft tissue B point, soft tissue pogonion, soft tissue menton and preaurale had especially small errors. Therefore, the Rapidform program can be considered a clinically efficient tool to produce and measure 3-D images. The soft tissue landmarks proposed above are mostly anatomically important points which are also easily reproducible. These landmarks can be beneficial in 3-D diagnosis and analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.1019-1022
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• 2012

Integral imaging is a promising technology for 3D imaging and display. Many parameters affect the performance of 3D integral imaging systems. Enhanced system performance is acquired by optimization of these system parameters with respect to defined performance metrics. In this paper, we present an approach to optimize the performance of 3D integral imaging system in terms of performance metrics under fixed resource constraints. In this analysis, system parameters such as lens numerical aperture, pitch between image sensors, the number of image sensors, the pixel size, and the number of pixels are determined to optimize performance metrics. Wave optics is utilized to describe the imaging process.