• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.219-221
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• 2007

Recent changes to ubiquitous computing requires more natural human-computer(HCI) interfaces that provide high information accessibility. Hand-gesture, i.e., gestures performed by one 'or two hands, is emerging as a viable technology to complement or replace conventional HCI technology. This paper deals with hand-posture recognition. Hand-posture database construction is important in hand-posture recognition. Human hand is composed of 27 bones and the movement of each joint is modeled by 23 degrees of freedom. Even for the same hand-posture,. grabbed images may differ depending on user's characteristic and relative position between the hand and cameras. To solve the difficulty in defining hand-postures and construct database effective in size, we present a method using a 3D hand model. Hand joint angles for each hand-posture and corresponding silhouette images from many viewpoints by projecting the model into image planes are used to construct the ?database. The proposed method does not require additional equations to define movement constraints of each joint. Also using the method, it is easy to get images of one hand-posture from many vi.ewpoints and distances. Hence it is possible to construct database more precisely and concretely. The validity of the method is evaluated by applying it to the hand-posture recognition system.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.8
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• pp.431-439
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• 2002

Due to the recent development of graphics hardware, real-time rendering of complex scenes is still a challenging task. As results of researches on image based rendering, the rendering schemes based on post-rendering 3D warping have been proposed. In general, these methods produce good rendering results. However, they are not appropriate for real-time rendering since it is not easy to accelerate the time-consuming algorithms within graphics subsystem. As an attempt to resolve this problem of the post-rendering 3D warping technique, we present a new real-time scheme based on projective texture. In our method, two reference images obtained by rendering complicated objects at two consecutive points of time are used. Rendering images of high quality for intermediate points of time are obtained by projecting the reference images onto a simplified object, and then blending the resulting images. Our technique will be effectively used in developing real-time graphics applications such as 3D games and virtual reality software and so on.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1658-1667
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• 2008

Reconstruction of 3D objects from a single view image is generally an ill-posed problem because of the projection distortion. A monocular vision based 3D object localization method is proposed in this paper, which approximates an object on the ground to a simple bounding solid and works automatically without any prior information about the object. A spherical or cylindrical object determined based on a circularity measure is approximated to a bounding cylinder, while the other general free-shaped objects to a bounding box or a bounding cylinder appropriately. For a general object, its silhouette on the ground is first computed by back-projecting its projected image in image plane onto the ground plane and then a base rectangle on the ground is determined by using the intuition that touched parts of the object on the ground should appear at lower part of the silhouette. The base rectangle is adjusted and extended until a derived bounding box from it can enclose the general object sufficiently. Height of the bounding box is also determined enough to enclose the general object. When the general object looks like a round-shaped object, a bounding cylinder that encloses the bounding box minimally is selected instead of the bounding box. A bounding solid can be utilized to localize a 3D object on the ground and to roughly estimate its volume. Usefulness of our approach is presented with experimental results on real image objects and limitations of our approach are discussed.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2E
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• pp.71-80
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• 2002

This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.2
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• pp.112-123
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• 1990

This paper presents a vertex-detecting of Hanguel patterns using nested contour shape. Inputed binary character patterns are transformed by distance transformation method and make a new file of transferred data by analysis of charactersitcs. A new vertex-detecting algorithm for recognizing Hanguel patterns using the two data files is proposed. This algorithm is able to reduce the projecting parts of Hanguel pattern, separate the connecting parts between different strokes, set the code number by transformed value of coorked features. It makes the output of results in order to apply the Hanguel recognition.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.838-855
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• 2019

Online product reviews are a vital source for companies in that they contain consumers' opinions of products. The earlier methods of opinion mining, which involve drawing semantic information from text, have been mostly applied in one dimension. This is not sufficient in itself to elicit reviewers' comprehensive views on products. In this paper, we propose a novel approach in opinion mining by projecting online consumers' reviews in a multidimensional framework to improve review interpretation of products. First of all, we set up a new framework consisting of six dimensions based on a marketing management theory. To calculate the distances of review sentences and each dimension, we embed words in reviews utilizing Google's pre-trained word2vector model. We classified each sentence of the reviews into the respective dimensions of our new framework. After the classification, we measured the sentiment degrees for each sentence. The results were plotted using a radar graph in which the axes are the dimensions of the framework. We tested the strategy on Amazon product reviews of the iPhone and Galaxy smartphone series with a total of around 21,000 sentences. The results showed that the radar graphs visually reflected several issues associated with the products. The proposed method is not for specific product categories. It can be generally applied for opinion mining on reviews of any product category.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.363-385
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• 1998

In orthodontics and orthognathic surgery. cephalogram has been routine practice in diagnosis and treatment evaluation of craniofacial deformity. But its inherent distortion of actual length and angles during projecting three dimensional object to two dimensional plane might cause errors in quantitative analysis of shape and size. Therefore, it is desirable that three dimensional object is diagnosed and evaluated three dimensionally and three dimensional CT image is best for three dimensional analysis. Development of clinic necessitates evaluation of result of treatment and comparison before and after surgery. It is desirable that patient that was diagnosed and planned by three dimensional computed tomography before surgery is evaluated by three dimensional computed tomography after surgery. too. But Because there is no standardized normal values in three dimension now and three dimensional Computed Tomography needs expensive equipments and because of its expenses and amount of exposure to radiation. limitations still remain to be solved in its application to routine practice. If postoperative three dimensional image is constructed by pre and postoperative lateral and postero-anterior cephalograms and preoperative three dimensional computed tomogram. pre and postoperative image will be compared and evaluated three dimensionally without three dimensional computed tomography after surgery and that will contribute to standardize normal values in three dimension. This study introduced new method that computer-simulated three dimensional image was constructed by preoperative three dimensional computed tomogram and pre and postoperative lateral and postero-anterior cephalograms. and for validation of new method. in four cases of dry skull that position of mandible was displaced and four patients of orthognathic surgery. computer-simulated three dimensional image and actual postoperative three dimensional image were compared. The results were as follows. 1. In four cases of dry skull that position of mandible was displaced. range of displacement between computer-simulated three dimensional images and actual postoperative three dimensional images in co-ordinates values was from -1.8 mm to 1.8 mm and 94％ in displacement of all co-ordinates values was from -1.0 mm to 1.0 mm and no significant difference between computer-simulated three dimensional images and actual postoperative three dimensional images was noticed(p>0.05). 2. In four cases of orthognathic surgery patients, range of displacement between computer­simulated three dimensional images and actual postoperative three dimensional images in coordinates values was from -6.7 mm to 7.7 mm and 90％ in displacement of all co-ordinates values was from -4.0 to 4.0 mm and no significant difference between computer-simulated three dimensional images and actual postoperative three dimensional images was noticed(p>0.05). Conclusively. computer-simulated three dimensional image was constructed by preoperative three dimensional computed tomogram and pre and postoperative lateral and postero-anterior cephalograms. Therefore. potentiality that can construct postoperative three dimensional image without three dimensional computed tomography after surgery was presented.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.1-9
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• 2016

In this paper we present a projection mapping system onto human's moving hand by a projector as information delivery media and Kinect to recognize hand motion. Most traditional projection mapping techniques project a variety of images onto stationary objects, however, our system provides new user experience by projecting images onto the center of the moving palm. We explain development process of the system, and production of content as applications on our system. We propose hardware organization and development process of open software architecture based on object oriented programming approach. For stable image projection, we describe a device calibration method between the projector and Kinect in three dimensional space, and a denoising technique to minimize artifacts from Kinect coordinates vibration and unstable hand tremor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.2
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• pp.120-133
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• 2008

This paper presents a novel approach for facial motion tracking and facial expression cloning to create a realistic facial animation of a 3D avatar. The exact head pose estimation and facial expression tracking are critical issues that must be solved when developing vision-based computer animation. In this paper, we deal with these two problems. The proposed approach consists of two phases: dynamic head pose estimation and facial expression cloning. The dynamic head pose estimation can robustly estimate a 3D head pose from input video images. Given an initial reference template of a face image and the corresponding 3D head pose, the full head motion is recovered by projecting a cylindrical head model onto the face image. It is possible to recover the head pose regardless of light variations and self-occlusion by updating the template dynamically. In the phase of synthesizing the facial expression, the variations of the major facial feature points of the face images are tracked by using optical flow and the variations are retargeted to the 3D face model. At the same time, we exploit the RBF (Radial Basis Function) to deform the local area of the face model around the major feature points. Consequently, facial expression synthesis is done by directly tracking the variations of the major feature points and indirectly estimating the variations of the regional feature points. From the experiments, we can prove that the proposed vision-based facial expression cloning method automatically estimates the 3D head pose and produces realistic 3D facial expressions in real time.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.252-260
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• 2016

The performance of human detection system is affected by camera location and view angle. In 2D image acquired from such camera settings, humans are displayed in different sizes. Detecting all the humans with diverse sizes poses a difficulty in realizing a real-time system. However, if the size of a human in an image can be predicted, the processing time of human detection would be greatly reduced. In this paper, we propose a method that estimates human size by constructing an indoor scene in 3D space. Since the human has constant size everywhere in 3D space, it is possible to estimate accurate human size in 2D image by projecting 3D human into the image space. Experimental results validate that a human size can be predicted from the proposed method and that machine-learning based detection methods can yield the reduction of the processing time.