• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.5
• /
• pp.518-528
• /
• 2014

In this paper, we propose a method to recognize the action direction of human by developing 4D space-time (4D-ST, [x,y,z,t]) features. For this, we propose 4D space-time interest points (4D-STIPs, [x,y,z,t]) which are extracted using 3D space (3D-S, [x,y,z]) volumes reconstructed from images of a finite number of different views. Since the proposed features are constructed using volumetric information, the features for arbitrary 2D space (2D-S, [x,y]) viewpoint can be generated by projecting the 3D-S volumes and 4D-STIPs on corresponding image planes in training step. We can recognize the directions of actors in the test video since our training sets, which are projections of 3D-S volumes and 4D-STIPs to various image planes, contain the direction information. The process for recognizing action direction is divided into two steps, firstly we recognize the class of actions and then recognize the action direction using direction information. For the action and direction of action recognition, with the projected 3D-S volumes and 4D-STIPs we construct motion history images (MHIs) and non-motion history images (NMHIs) which encode the moving and non-moving parts of an action respectively. For the action recognition, features are trained by support vector data description (SVDD) according to the action class and recognized by support vector domain density description (SVDDD). For the action direction recognition after recognizing actions, each actions are trained using SVDD according to the direction class and then recognized by SVDDD. In experiments, we train the models using 3D-S volumes from INRIA Xmas Motion Acquisition Sequences (IXMAS) dataset and recognize action direction by constructing a new SNU dataset made for evaluating the action direction recognition.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.10
• /
• pp.293-302
• /
• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.5
• /
• pp.404-411
• /
• 2009

We introduce in this paper a new method for smooth foldover-free warping of images, based on the vector field deformation technique proposed by Von Funck et al. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of a point in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. From the user-specified constraints, it computes in the image domain a C1-continuous velocity vector field, along which each pixel progressively moves from its original position to the target. The target positions of the pixels are obtained by solving a set of partial derivative equations with the 4th order Runge-Kutta method. We show how our method can be useful for texture mapping with hard constraints. We start with an unconstrained planar embedding of a target mesh using a previously known method (Least Squares Conformal Map). Then, in order to obtain a texture map that satisfies the given constraints, we use the proposed warping method to align the features of the texture image with those on the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping, offers higher level of control for defining the constraints, and is simpler to implement.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.5
• /
• pp.441-446
• /
• 2020

In this paper, we propose the α-Feature Map Scaling (α-FMS) method which extends the FMS method that was designed to enhance the discriminative power of feature maps of deep neural networks in Speaker Verification (SV) systems. The FMS derives a scale vector from a feature map and then adds or multiplies them to the features, or sequentially apply both operations. However, the FMS method not only uses an identical scale vector for both addition and multiplication, but also has a limitation that it can only add a value between zero and one in case of addition. In this study, to overcome these limitations, we propose α-FMS to add a trainable parameter α to the feature map element-wise, and then multiply a scale vector. We compare the performance of the two methods: the one where α is a scalar, and the other where it is a vector. Both α-FMS methods are applied after each residual block of the deep neural network. The proposed system using the α-FMS methods are trained using the RawNet2 and tested using the VoxCeleb1 evaluation set. The result demonstrates an equal error rate of 2.47 % and 2.31 % for the two α-FMS methods respectively.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.1
• /
• pp.133-138
• /
• 2006

Electronic Navigational Charts(ENCs) are official nautical charts which are equivalent to paper charts with supplementary information. Although their main purpose is to be used for the safe navigation of ships, they also contain much information on coasts and seas which may be interesting to ordinary people. However, there is no easy way to access them because of therir specialized data format, access method and visualization. This paper proposes on implementation of SVG for the access and services of ENCs. SVG(Scalable Vector Graphic) makes it possible to make use of Vector graphics for servicing maps in basic internet browsing environment. Implement of SVG for ENC applications by this research is free of special server side GIS mapping system and client side extra technology. The implementation of SVG for ENC Applications can be summarized as follows: Firstly, SVG provides spatial information to possess searching engine to embody SVG map. Secondly, SVG can provide high-quality vector map graphics and interactive facility without special Internet GIS system. It makes it possible to use services with very low cost. Thirdly, SVG information service targeting on maritime transportation can be used as template, so it can be used dynamically any other purpose such as traffic management and vessel monitoring. Many good characteristics of SVG in mapping at computer screen and reusability of SVG document provide new era of visualization of marine geographic information.

• The Journal of Engineering Research
• /
• v.5 no.1
• /
• pp.17-35
• /
• 2004

Svg(Scalable Vector Graphics) is xml graphic standard recommended by E3C as a language based on xml to express two-dimension graphic. Svg can accommodate all Xml's patency and advantage of interoperability, and can used as various web applications being combined with other xml language. In addition, Svg can be applied to the fields of electronic commerce, geographical information, computer education and advertisement because it can produce high quality of dynamic from real-time data. SVG's application can be enhanced by linking with database. In this paper, we discuss how Svg can be utilized in theater reservation system, not just explaining svg's meaning or ability. Svg added graphic advantage in addition to xml's advantage. This means that svg retains not only graphic element but also xml's softness. It becomes easier to designate seats and add them. Current reservation system provided in general only information on time and price for a ticket, but the system using SVG in this paper provides additional information on position, price, cancellation and purchase availability of seat.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.10
• /
• pp.1930-1936
• /
• 2007

Electronic Navigational Charts(ENCs) are official nautical charts which are equivalent to paper charts with supplementary information. Although their main purpose is to be used for the safe navigation of ships, they also contain much information on coasts and seas which may be interesting to ordinary people. However, there is no easy way to access them because of their specialized data format, access method and visualization. This paper proposes m implementation of SVG for the access and services of ENCs. SVG(Scalable Vector Graphic) makes it possible to make use of Vector graphics for map services in basic internet browsing environment. Implementation of SVG for ENC applications by this research is free of special server side GIS mapping system and client side extra technology. The Implementation of SVG for ENC Applications can be summarized as follows: Firstly, SVG provides spatial information to possess searching engine to embody SVG map. Secondly SVG can provide high-quality vector map graphics and interactive facility without special Internet GIS system. It makes it possible to use services with very low cost. Thirdly, SVG information service targeting on maritime transportation can be used as template, so it can be used dynamically any other purpose such as traffic management and vessel monitoring. Many good characteristics of SVG in mapping at computer screen and reusability of SVG document provide new era of visualization of marine geographic information.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.2
• /
• pp.113-130
• /
• 2004

Most multimedia data contain text to emphasize the meaning of the data, to present additional explanations about the situation, or to translate different languages. But, the left makes it difficult to reuse the images, and distorts not only the original images but also their meanings. Accordingly, this paper proposes a support vector machines (SVMs) and spatiotemporal restoration-based approach for automatic text detection and removal in video sequences. Given two consecutive frames, first, text regions in the current frame are detected by an SVM-based texture classifier Second, two stages are performed for the restoration of the regions occluded by the detected text regions: temporal restoration in consecutive frames and spatial restoration in the current frame. Utilizing text motion and background difference, an input video sequence is classified and a different temporal restoration scheme is applied to the sequence. Such a combination of temporal restoration and spatial restoration shows great potential for automatic detection and removal of objects of interest in various kinds of video sequences, and is applicable to many applications such as translation of captions and replacement of indirect advertisements in videos.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.3
• /
• pp.1-9
• /
• 2014

In this paper, we design and implement location information system and user mapping system using DSDV(Destination Sequenced Distance Vector) routing algorithm in ad-hoc network environment to efficient manage a number of mobile devices. The software part in proposed system construct ad-hoc network using DSDV routing algorithm and it activate alarm system, such as vibration, when one of devices disappears in the network. The hardware system, called u_LIN (User Location Information Node) construct ad-hoc network and it helps to find a disappeared device by using warning system. When we evaluate the performance of our prototype system, we have checked a correct operation, within the range of 250m in case of 1:1 communication and within the range of 100m in case of 1:N communication. The implemented system in this paper is highly expected to flexibly use in juvenile protection system, stray-child protection system, tourist guide system and so on.

• Journal of Internet Computing and Services
• /
• v.18 no.6
• /
• pp.35-46
• /
• 2017

Recently, attackers using malicious code in cyber security have been increased by attaching malicious code to a mail and inducing the user to execute it. Especially, it is dangerous because it is easy to execute by attaching a document type file. The author analysis is a research area that is being studied in NLP (Neutral Language Process) and text mining, and it studies methods of analyzing authors by analyzing text sentences, texts, and documents in a specific language. In case of attack mail, it is created by the attacker. Therefore, by analyzing the contents of the mail and the attached document file and identifying the corresponding author, it is possible to discover more distinctive features from the normal mail and improve the detection accuracy. In this pager, we proposed IADA2(Intelligent Attack mail Detection based on Authorship Analysis) model for attack mail detection. The feature vector that can classify and detect attack mail from the features used in the existing machine learning based spam detection model and the features used in the author analysis of the document and the IADA2 detection model. We have improved the detection models of attack mails by simply detecting term features and extracted features that reflect the sequence characteristics of words by applying n-grams. Result of experiment show that the proposed method improves performance according to feature combinations, feature selection techniques, and appropriate models.