• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1469-1473
• /
• 2004

We suggest how to program off-line robot path along shoes' outsole shape in the footwear buffing process by a 5-axis microscribe system like robot arms. This microscribe system developed consists a 5-axis robot link with a turn table, signal processing circuit, PC and an application software program. It makes a robot path on the shoe's upper through the movement of a microscribe with many joints. To do this, first it reads 5-encoder's pulse values while a robot arm points a shoes' outsole shape from the initial status. This system developed calculates the encoder pulse values for the robot arm's rotation and transmits the angle pulse values to the PC through a circuit. Then, Denavit-Hartenberg's(D-H) direct kinematics is used to make the global coordinate from robot joint one. The determinant is obtained with kinematics equation and D-H variable representation. To drive the kinematics equation, we have to set up the standard coordinates first. The many links and the more complicated structure cause the difficult kinematics problem to solve in the geometrical way. Thus, we can solve the robot's kinematics problems efficiently and systematically by Denavit-Hartenberg's representation. Finally, with the coordinate values calculated above, it can draw a buffing gauge-line on the upper. Also, it can program off-line robot path on the shoes' upper. We are subjected to obtaining shoes' outline points, which are 2 outlines coupled with the points and the normal vector based on the points. These data is supposed to be transformed into .dxf file to be used for data of automatic buffing robot. This system developed is simulated by using spline curves coupled with each point from dxf file in Autocad. As a result of applying this system to the buffing robot in the flexible footwear manufacturing system, it can be used effectively to program the path of a real buffing robot.

• Journal of KIISE:Software and Applications
• /
• v.31 no.1
• /
• pp.71-81
• /
• 2004

Minutiae-based fingerprint identification systems use minutiae points, which cannot completely characterize local ridge structures. Further, this method requires many methods for matching two fingerprint images containing different number of minutiae points. Therefore, to represent the fired length information for one fingerprint image, the filterbank-based method was proposed as an alternative to minutiae-based fingerprint representation. However, it has two shortcomings. One shortcoming is that similar feature vectors are extracted from the different fingerprints which have the same fingerprint type. Another shortcoming is that this method has overload to reduce the rotation error in the fingerprint image acquisition. In this paper, we propose the minutia-weighted feature vector extraction method that gives more weight in extracting feature value, if the region has minutiae points. Also, we Propose new fingerprint alignment method that uses the average local orientations around the reference point. These methods improve the fingerprint system's Performance and speed, respectively. Experimental results indicate that the proposed methods can reduce the FRR of the filterbank-based fingerprint matcher by approximately 0.524% at a FAR of 0.967%, and improve the matching performance by 5% in ERR. The system speed is over 1.28 times faster.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.44 no.11
• /
• pp.965-972
• /
• 2016

This paper presents results of flight experiments on a navigation algorithm including multiplicative extended Kalman filter for estimating attitude of the guided munition. The filter describes orientation of aircraft by data fusion with low-cost sensors where measurement update is done by multiplication, rather than addition, which is suitable for quaternion representation. In determining attitude from vector observations, the existing approach utilizes a 3-axis accelerometer as a 2-axis inclinometer by measuring gravity to estimate pitch and roll angles, while GNSS velocity is used to derive heading of the vehicle. However, during accelerated maneuvers such as coordinated flight, the accelerometer provides inadequate inclinometer measurements. In this paper, the measurement update process is newly defined to complement the vulnerability by using different vector observations. The acceleration measurement is considered as a result of a centrifugal force and gravity during turning maneuvers and used to estimate roll angle. The effectiveness of the proposed method is verified through flight experiments.

• Journal of the HCI Society of Korea
• /
• v.1 no.1
• /
• pp.37-44
• /
• 2006

Specular reflections provide the visual feedback that describes the material type of an object, its local shape, and lighting environment. In photorealistic rendering, there have been a number of research available to render specular reflections effectively based on a local reflection model. In traditional cel animations and cartoons, specular reflections plays important role in representing artistic intentions for an object and its related environment reflections, so the shapes of highlights are quite stylistic. In this paper, we present a method to render and control stylized specular reflections using projective textures based on principal curvature analysis. Specifying a texture as a pattern of a highlight and projecting the texture on the specular region of a given 3D model, we can obtain a stylized representation of specular reflections. For a given polygonal model, a view point, and a light source, we first find the maximum specular intensity point, and then locate the texture projector along the line parallel to the normal vector and passing through the point. The orientation of the projector is determined by the principal directions at the point. Finally, the size of the projection frustum is determined by the principal curvatures corresponding to the principal directions. The proposed method can control the position, orientation, and size of the specular reflection efficiently by translating the projector along the principal directions, rotating the projector about the normal vector, and scaling the principal curvatures, respectively. The method is be applicable to real-time applications such as cartoon style 3D games. We implement the method by Microsoft DirectX 9.0c SDK and programmable vertex/pixel shaders on Nvidia GeForce FX 7800 graphics subsystems. According to our experimental results, we can render and control the stylized specular reflections for a 3D model of several ten thousands of triangles in real-time.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.8
• /
• pp.783-790
• /
• 2019

Cognitive science attempts to explain human intelligence on the basis of success of artificial neural network, which is called connectionism. The neural network, e.g., deep learning, seemingly promises connectionism to go beyond what it is. But those(Fodor & Pylyshyn, Fodor, & McLaughlin) who advocate classical computationalism, or symbolism claim that connectionism must fail since it cannot represent the relation between human thoughts and human language. The neural network lacks systematicity, so any output of neural network is at best association or accidental combination of data plugged in input units. In this paper, I first introduce structure of artificial neural network and what connectionism amounts to. Second, I shed light on the problem of systematicity the classical computationalists pose for the connectionists. Third, I briefly introduce how those who advocate connectionism respond to the criticism while noticing Smolensky's theory of vector product. Finally, I examine the debate of computationalism and connectionism on systematicity, and show how the problem of systematicity contributes to the development of connectionism and computationalism both.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.6
• /
• pp.183-190
• /
• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1730-1747
• /
• 2018

Multi-view video plus depth (MVD) is a mainstream format of 3D scene representation in free viewpoint video systems. The advanced 3D extension of the high efficiency video coding (3D-HEVC) standard introduces new prediction tools to improve the coding performance of depth video. However, the depth video in 3D-HEVC is time consuming. To reduce the complexity of the depth video inter coding, we propose a fast coding unit (CU) size and mode decision algorithm. First, an off-line trained Bayesian model is built which the feature vector contains the depth levels of the corresponding spatial, temporal, and inter-component (texture-depth) neighboring largest CUs (LCUs). Then, the model is used to predict the depth level of the current LCU, and terminate the CU recursive splitting process. Finally, the CU mode search process is early terminated by making use of the mode correlation of spatial, inter-component (texture-depth), and inter-view neighboring CUs. Compared to the 3D-HEVC reference software HTM-10.0, the proposed algorithm reduces the encoding time of depth video and the total encoding time by 65.03% and 41.04% on average, respectively, with negligible quality degradation of the synthesized virtual view.

• The Journal of Information Technology
• /
• v.7 no.4
• /
• pp.1-8
• /
• 2004

The depth information of 3D image lost by projecting 3D-object to 2D-screen for earning image. If depth information is restored and is used to recognize 3D-object, we can make the more effective recognition system. We often use shape from stereo algorithm in order to restore this information. In this paper, we suggest 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In this system, we use the moving vector of object to reduce matching time and In second matching step, the unknown input image is compared with the reference images, which is made with octree codes. Octree codes are used in volume-based representation of a three dimensional object. The result of simulation show that the proposed 3-D object recognition system provides satisfactory performance.

• Journal of Korea Multimedia Society
• /
• v.15 no.4
• /
• pp.485-491
• /
• 2012

This paper proposes 'Coding Unit Tree' based on quadtree efficiently with motion vector to represent splitting information of a Coding Unit (CU) in HEVC. The new international video coding, High Efficiency Video Coding (HEVC), adopts various techniques and new unit concept: CU, Prediction Unit (PU), and Transform Unit (TU). The basic coding unit, CU is larger than macroblock of H.264/AVC and it splits to process image-based quadtree with a hierarchical structure. However, in case that there are complex motions in CU, the more signaling bits with motion information need to be transmitted. This structure provides a flexibility and a base for a optimization, but there are overhead about splitting information. This paper analyzes those signals and proposes a new algorithm which removes those redundancy. The proposed algorithm utilizes a type code, a dominant value, and residue values at a node in quadtree to remove the addition bits. Type code represents a structure of an image tree and the two values represent a node value. The results show that the proposed algorithm gains 13.6% bit-rate reduction over the HM-1.0.

• Journal of KIISE:Software and Applications
• /
• v.35 no.8
• /
• pp.522-528
• /
• 2008

Topic map typically provide information to user through the selection of topics, that is using only topic, association, occurrence on the first topicmap which is made by domain expert without regard to individual interests or context, for the purpose of supplementation for the weakness which is providing personalized topic map information, personalization has been studied for supporting user preference through preseting of customize, filtering, scope, etc in topic map. Nevertheless, personalization in current topicmap is not enough to user so far. In this paper, we propose a design of PTRS(personalized topicmap ranking system) & algorithm, using both user profile(click through data) and basic element of topic map(topic, association) on knowledge layer in specific domain topicmap, therefore User has strong point that is improvement of personal facilities to user through representation of ranked topicmap information in consideration of user preference using PTRS.