• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.135-141
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• 2008

In this paper, we propose colored-hear recognition that distinguishing feature of synesthesia for human sensing by shared vision and specific sense of hearing. We perceived what potential influence of human's structured object recognition by visual analysis through the camera, So we've studied how to make blind persons can feel similar vision of real object. First of all, object boundaries are detected in the image data representing a specific scene. Then, four specific features such as object location in the image focus, feeling of average color, distance information of each object, and object area are extracted from picture. Finally, mapping these features to the audition factors. The audition factors are used to recognize vision for blind persons. Proposed colored-hear transformation for recognition can get fast and detail perception, and can be transmit information for sense at the same time. Thus, we were get a food result when applied this concepts to blind person's case of image recognition.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.43-49
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• 2023

Object tracking is being studied with various techniques such as Kalman filter and Luenberger tracker. Even in situations, such as the one in which the system model is not well specified, to which existing signal processing techniques are not successfully applicable, it is possible to design artificial neural networks to track objects. In this paper, we propose an artificial neural network, which we call 'maximum-likelihood weighted-average neural network', to continuously track unpredictably moving objects. This neural network does not directly estimate the locations of an object but obtains location estimates by making weighted average combining various results of maximum likelihood tracking with different data lengths. We compare the performance of the proposed system with those of Kalman filter and maximum likelihood object trackers and show that the proposed scheme exhibits excellent performance well adapting the change of object moving characteristics.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.66-77
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• 2006

In this paper, we researched the searching and tracking locations of a home resident using ON/OFF switches and sensors and designed a remote monitoring system. As an implementation environment, this system is developed on the base of the distributed object group framework we have developed from previous works. In order to trace the moving locations of a home resident, we firstly showed a home structure which attaches ON/OFF switches and sensors to home appliances and indoor facilities being fixed in home. Whenever a home resident opens/closes these objects, the signals operated from ON/OFF switches and sensors are sent to a home server system. In this time, the real locations of ON/OFF switches and sensors that the signals are being occurred must be the current location that he/she stays. A home server system provides the functionalities that map the real location of a resident in home to virtual location designed on remote desk-tops or terminals like PDAs, and that construct a healthcare database consisted of moving patterns, moving ranges, momentum for analyzing the given searching locations and times Finally, this system provides these information for remotely monitoring services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.179-187
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• 2015

Spread of smartphone creates various contents. Among many contents, AR application using Location Based Service(LBS) is needed widely. In this paper, we propose error correction algorithm for location-based Augmented Reality(AR) system using computer vision technology in android environment. This method that detects the early features with SURF(Speeded Up Robust Features) algorithm to minimize the mismatch and to reduce the operations, and tracks the detected, and applies it in mobile environment. We use the GPS data to retrieve the location information, and use the gyro sensor and G-sensor to get the pose estimation and direction information. However, the cumulative errors of location information cause the mismatch that and an object is not fixed, and we can not accept it the complete AR technology. Because AR needs many operations, implementation in mobile environment has many difficulties. The proposed approach minimizes the performance degradation in mobile environments, and are relatively simple to implement, and a variety of existing systems can be useful in a mobile environment.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.147-155
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• 2011

Map rendering, positioning, database managements are key elements of location based services. Google map and GPS (Global Positioning System) have become a very popular solution for map rendering and positioning, respectively. They are very effective and yet free of charge. However, they cannot be used for an indoor location based service system. We cannot render a building drawing with Google map, we cannot determine a moving object's position when it is indoor. This paper introduces our web services of rendering drawings, indoor positioning, and multimedia contents up-loading and playing so that any programmers can use them in developing indoor location based service systems. In order to experimentally show the efficiency of our web services, we have built a location based contents displaying system for museum visitors with them.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.619-630
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• 2017

With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.169-172
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• 2013

Building Information Modeling (BIM) is an effective decision-making platform that helps to save project cost and enhance quality of construction. By generating and linking a wide variety of objects data, BIM can be effectively utilized, and it should be ensured that object properties maintain consistency throughout the project period of design, estimates, construction, maintenance and repair. This study examined how to utilize BIM data in a construction project, by linking cost and schedule data in web environment, to better utilize the information and maintain consistency of the BIM information. To do so, the model integrated WBS data and CBS data, linked them with BIM model to realize 5D simulation in web environment. As a result, cost and schedule data could be simultaneously acquired, and object properties-cost, schedule, location-as well. These are expected to contribute to developing a BIM-based automatic data-processing system in web environment.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1022-1030
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• 2006

The location awareness is an important part of many ubiquitous computing systems, but a perfect location system does not exist yet in spite of many researches. Among various location tracking systems, we choose the RFID system due to its wide applications. However, the sensed RSSI signal is too sensitive to the direction of a RFID reader antenna, the orientation of a RFID tag, the human interference, and the propagation media situation. So, the existing location tracking method in spite of using the particle filter is not working well. To overcome this shortcoming, we suggest a robust location tracking method with a double layered structure, where the first layer coarsely estimates a tag's location in the block level using a regression technique or the SVM classifier and the second layer precisely computes the tag's location, velocity and direction using the particle filter technique. Its layered structure improves the location tracking performance by restricting the moving degree of hidden variables. Many extensive experiments show that the proposed location tracking method is so precise and robust to be a good choice for implementing the location estimation of a person or an object in the ubiquitous computing. We also validate the usefulness of the proposed location tracking method by implementing it for a real-time people monitoring system in a noisy and complicate workplace.

• Journal of the Korean housing association
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• v.18 no.2
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• pp.75-82
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• 2007

Under the premise that the housing market is not fixed, but changes organically according to social and systematic environment, it has important meaning as the object of this study to identify the recent housing market's movement by deducing the changed characteristics of the factors to compose the recent new houses. By using the following methodology, this study analyzed the characteristics and mutual relations of the economical and house-composing factors, categorized the investigation object into sub-markets, and executed comparative analysis. First, based on the leading studies analyzing the factors of house price determination and the assessment indicators of 'Green Building Certification Program', the composing factors are deduced. Second, the factors are categorized as economic, housing complex planning and geographical condition. Third, to identify the influence of housing environmental factors on economic factors, the correlation between the former and the latter, and the difference between economic factors are analyzed. Fourth, by segmenting and categorizing the housing market into time and location subgroups, the chronicle trend and the geographical characteristics are analyzed.