• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.87-94
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• 2019

Recently, the advance of accurate dynamic displacement measurement devices, such as GPS, computer vision, and optic laser sensor, has enhanced the structural monitoring technology. In this study, the dynamic displacement data was used to verify the applicability of the structural physical parameter estimation method through subspace system identification. The subspace system identification theory for estimating state-space model from measured data and physics-based interpretation for deriving the physical parameter of the estimated system are presented. Three-degree-freedom steel structures were fabricated for the experimental verification of the theory in this study. Laser displacement sensor and accelerometer were used to measure the displacement data of each floor and the acceleration data of the shaking table. Discrete state-space model generated from measured data was verified for precision. The discrete state-space model generated from the measured data extracted the floor stiffness of the building after accuracy verification. In addition, based on the story stiffness extracted from the state space model, five column stiffening and damage samples were set up to extract the change rate of story stiffness for each sample. As a result, in case of reinforcement and damage under the same condition, the stiffness change showed a high matching rate.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.713-723
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• 2017

Since the panoramic image can overcome the limitation of the viewing angle of the camera and have a wide field of view, it has been studied effectively in the fields of computer vision and stereo camera. In order to generate a panoramic image, stitching images taken by a plurality of general cameras instead of using a wide-angle camera, which is distorted, is widely used because it can reduce image distortion. The image stitching technique creates descriptors of feature points extracted from multiple images, compares the similarities of feature points, and links them together into one image. Each feature point has several hundreds of dimensions of information, and data processing time increases as more images are stitched. In particular, when a panorama is generated on the basis of an image photographed by a plurality of unspecified cameras with respect to an object, the extraction processing time of the overlapping feature points for similar images becomes longer. In this paper, we propose a preprocessing process to efficiently process stitching based on an image obtained from a number of unspecified cameras for one object or environment. In this way, the data processing time can be reduced by pre-grouping images based on camera sensor information and reducing the number of images to be stitched at one time. Later, stitching is done hierarchically to create one large panorama. Through the grouping preprocessing proposed in this paper, we confirmed that the stitching time for a large number of images is greatly reduced by experimental results.

• Cartoon and Animation Studies
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• s.29
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• pp.151-172
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• 2012

Game production education in a university is very important because it is the stage for completing a game education course as well as for determining a future of game industry. In order to perform various experience and creative learning, it should be able to effectively use a computer infrastructure representing the knowledge and information society for the purpose of obtaining and re-processing information necessary for game production through prediction of directions of game industry as well information technology. This research is focused on an effective game engine education for students whom want to become game graphics designers. The purpose of this study is to draw a lesson of game production utilizing game engines and it enables practice-focused class for game production. It also allows the class participant to manufacture prototypes without support from game programmers for their outcomes of works planned during the game production class. The theoretical background of game production compared and analyzed exemplary game engines. Based on the result, the study selected Unity 3D engine and conducted the research on the background where the Unity engine has been selected and its characteristics. In addition, this study provided an example of game production utilizing a game engine, and also described the details of actual realization. This study selected Torque3D with the Unity in order to identify the purpose of this study and efficiency of learning. Thus, the previous situation is that the class remained in making a game plan during the course of game production project and, students whose major is not game programming. Now, it is necessary for students to make many efforts to make a game in an active and positive attitude by utilizing a game engine beyond the previous method of class.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.15-23
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• 2017

The person Re-identification is the most challenging part of computer vision due to the significant changes in human pose and background clutter with occlusions. The picture from non-overlapping cameras enhance the difficulty to distinguish some person from the other. To reach a better performance match, most methods use feature selection and distance metrics separately to get discriminative representations and proper distance to describe the similarity between person and kind of ignoring some significant features. This situation has encouraged us to consider a novel method to deal with this problem. In this paper, we proposed an enhanced recurrent neural network with three-tier hierarchical network for person re-identification. Specifically, the proposed recurrent neural network (RNN) model contain an iterative expectation maximum (EM) algorithm and three-tier Hierarchical network to jointly learn both the discriminative features and metrics distance. The iterative EM algorithm can fully use of the feature extraction ability of convolutional neural network (CNN) which is in series before the RNN. By unsupervised learning, the EM framework can change the labels of the patches and train larger datasets. Through the three-tier hierarchical network, the convolutional neural network, recurrent network and pooling layer can jointly be a feature extractor to better train the network. The experimental result shows that comparing with other researchers' approaches in this field, this method also can get a competitive accuracy. The influence of different component of this method will be analyzed and evaluated in the future research.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.83-93
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• 2013

Recently, the SURF algorithm, which is conjugated for object tracking system as part of many computer vision applications, is a well-known scale- and rotation-invariant feature detection algorithm. The SURF, due to its high computational complexity, there is essential to develop a hardware accelerator in order to be used on an IP in embedded environment. However, the SURF requires a huge local memory, causing many problems that increase the chip size and decrease the value of IP in ASIC and SoC system design. In this paper, we proposed a way to design a SURF algorithm in hardware with greatly reduced local memory by partitioning the algorithms into several Sub-IPs using external memory and a DMA. To justify validity of the proposed method, we developed an example of simplified object tracking algorithm. The execution speed of the hardware IP was about 31 frame/sec, the logic size was about 74Kgate in the 30nm technology with 81Kbytes local memory in the embedded system platform consisting of ARM Cortex-M0 processor, AMBA bus(AHB-lite and APB), DMA and a SDRAM controller. Hence, it can be used to the hardware IP of SoC Chip. If the image processing algorithm akin to SURF is applied to the method proposed in this paper, it is expected that it can implement an efficient hardware design for target application.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.19-25
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• 2020

As the number of mobile device users increases, research on various user authentication methods has been actively conducted to protect sensitive personal information. Knowledge-based techniques have the disadvantage that security is deteriorated due to easy exposure of authentication means, and proprietary-based techniques have a problem of increasing construction cost and low user convenience to use the service. In order to solve this problem, a FIDO authentication system, which is a user authentication method using a smart device, has been proposed. Since the FIDO authentication system performs authentication based on the biometric information of the user, the risk of the authentication means being leaked is low, and since the authentication information is stored in the user's smart device, the user information due to server hacking is solved. Through this, it is possible to select and utilize user authentication technology suitable for the security level of the service. In this paper, we introduce the FIDO authentication system, explain the main parts required for FIDO UAF client-server development, and show examples of implementation using UAF open source provided by ebay.

• Cross-Cultural Studies
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• v.19
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• pp.39-77
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• 2010

The cinema of Peter Greenaway has consistently engaged questions of the relationship between the arts and particularly the relations of image and writing to cinema. When different types of images are correlated and merged with each other on the borders of painting, photography, film, video and computer animation, the interrelationships of the distinct elements cause a shift in the notion of the whole image. This analysis proposes to articulate the complex relationship between the 'interartial' dimension and the 'intermedial' dimension in Peter Greenaway's film, (1991). If the interartiality is interested in the interaction between various arts, including the transition from one to another, the intermediality articulates the same type of relationship between two or more media. The interactional relationship is the same on both sides; on the contrary, the relationship between art and media does not show the same symmetry. All art is based on one or more media - the media is a condition existence of art - but no art can't be reduced to the status of media. This suggests that if the interartiality always involves the intermediality, this proposal may not be reversed. First, we analyse a self-conscious investigation into digital art and technology. Prosospero's Books can be read as a daring visual essay that self-consciously investigates the technical and philosophical functions of letters, books, images, animated paintings, digital arts, and the other magical illusions, which have been modern or will be post-modern media to represent the world. Greenaway uses both conventional film techniques and the resources of high-definition television to layer image upon image, superimposing a second or third frame within his frame. Greenaway uses the frame-within-frame as the cinematic equivalent of Shakespeare's paly-within-play : it offer him the possibility to analyse the work of art/artist/spectator relationship. Secondly, we analyse the relationship between the written word, oral word and the books. Like the written word, the oral word changes into a visual image: The linguistic richness and nuances of Shakeaspeare's characters turn into the powerful and authoritative, but monotone, voices of Gielgud-Prospero, who speaks the Shakespearean lines aloud, shaping the characters so powerfully through his worlds that they are conjured before us. Specially each book is placed over the frame of the play's action, only partially covering the image, so that it gives virtually every frame at least two space-time orientations. Thirdly, we try to show how Peter Greenaway uses pictorial references in order to illustrate the context of the Renaissance as well as pictorial techniques and language in order to question the nature of artistic representation. For exemple, The storm is visualised through reference to Botticelli's : the storm of papers swirling around the library is constructed to look like a facsimili copy of Michelangelo's Laurentiana Library in Florence. Greenaway's modern mannerism consists in imposing his own aesthetic vision and his questioning of art beyond the play's meta-theatricality: in other words, Shakespeare''s text has been adapted without being betrayed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.161-170
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• 2019

Multi-product mass production small and medium enterprise factories have a wide variety of products and a large number of products, wasting manpower and expenses for inventory management. In addition, there is no way to check the status of inventory in real time, and it is suffering economic damage due to excess inventory and shortage of stock. There are many ways to build a real-time data collection environment, but most of them are difficult to afford for small and medium-sized companies. Therefore, smart factories of small and medium enterprises are faced with difficult reality and it is hard to find appropriate countermeasures. In this paper, we implemented the contents of extension of existing inventory management method through character extraction on label with barcode and QR code, which are widely adopted as current product management technology, and evaluated the effect. Technically, through preprocessing using OpenCV for automatic recognition and classification of stock labels and barcodes, which is a method for managing input and output of existing products through computer image processing, and OCR (Optical Character Recognition) function of Google vision API. And it is designed to recognize the barcode through Zbar. We propose a method to manage inventory by real-time image recognition through Raspberry Pi without using expensive equipment.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.