• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.155-160
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• 2010

In this paper, we proposed a forensic mark algorithm which can embed the distributor's information at each distribution step to trace the illegal distribution path. For this purpose, the algorithm has to have the high capacity payload for embedding the copyright and user information at each step, and the embedded information at a step should not interfere with the information at other step. The proposed algorithm can trace the multilevel distribution because the forensic mark is generated by digital hologram and embedded in the DWT-SVD domain. For the high capacity embedding, the off-axis hologram is generated from the forensic mark and the hologram is embedded in the HL, LH, HH bands of the DWT to reduce the signal interference. The SVD which is applied the holographic signal enhanced the detection performance and the safety of the forensic mark algorithm. As the test results, this algorithm was able to embed 128bits information for the copyright and user information at each step. In this paper, we can embed total 384bits information for 3 steps and the algorithm is also robust to the JPEG compression.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.411-417
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• 2009

We proposed a robust body part tracking system for intelligent environment that will not limit freedom of users. Unlike any previous gesture recognizer, we upgraded the generality of the system by creating the ability the ability to recognize details, such as, the ability to detect the difference between long sleeves and short sleeves. For the precise each body part tracking, we obtained the image of hands, head, and feet separately from a single camera, and when detecting each body part, we separately chose the appropriate feature for certain parts. Using a calibrated camera, we transferred 2D detected body parts into the 3D posture. In the experimentation, this system showed advanced hand tracking performance in real time(50fps).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.586-599
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• 2012

This paper proposes a fast face detection and tracking method which uses depth images as well as RGB images. It consists of the face detection procedure and the face tracking procedure. The face detection method basically uses an existing method, Adaboost, but it reduces the size of the search area by using the depth image. The proposed face tracking method uses a template matching technique and incorporates an early-termination scheme to reduce the execution time further. The results from implementing and experimenting the proposed methods showed that the proposed face detection method takes only about 39% of the execution time of the existing method. The proposed tracking method takes only 2.48ms per frame with $640{\times}480$ resolution. For the exactness, the proposed detection method showed a little lower in detection ratio but in the error ratio, which is for the cases when a detected one as a face is not really a face, the proposed method showed only about 38% of that of the previous method. The proposed face tracking method turned out to have a trade-off relationship between the execution time and the exactness. In all the cases except a special one, the tracking error ratio is as low as about 1%. Therefore, we expect the proposed face detection and tracking methods can be used individually or in combined for many applications that need fast execution and exact detection or tracking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.636-644
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• 2015

This research aims to suggest methods to improve object tracking performance by combining CAM shift algorithm with 8-way search window, and reduce arithmetic operation by reducing the number of frame used for tracking. CAM shift has its adverse effect in tracking methods using signature color or having difficulty in tracking rapidly moving object. To resolve this, moving search window of CAM shift makes it possible to more accurately track high-speed moving object after finding object by conducting 8-way search by using information at a final successful timing point from a timing point missing tracking object. Moreover, hardware development led to increased unnecessary arithmetic operation by increasing the number of frame produced per second, which indicates efficiency can be enhanced by reducing the number of frame used in tracking to reduce unnecessary arithmetic operation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.9-20
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• 2005

In this paper, we propose ubiTrack, a system which tracks users' location in indoor environments by employing infrared-based proximity method. Most of recently developed systems have focussed on performance and accuracy. For this reason, they adopted the idea of centralized management, which gathers all information in a main system to monitor users' location. However, these systems raise privacy concerns in ubiquitous computing environments where tons of sensors are seamlessly embedded into environments. In addition, centralized systems also need high computational power to support multiple users. The proposed ubiTrack is designed as a passive mobile architecture to relax privacy problems. Moreover, ubiTrack utilizes appropriate area as a unit to efficiently track users. To achieve this, ubiTrack overlaps each sensing area by utilizing the TDM (Time-Division Multiplexing) method. Additionally, ubiTrack exploits various filtering methods at each receiver and utilization module. The filtering methods minimize unexpected noise effect caused by external shock or intensity weakness of ID signal at the boundary of sensing area. ubiTrack can be applied not only to location-based applications but also to context-aware applications because of its associated module. This module is a part of middleware to support communication between heterogeneous applications or sensors in ubiquitous computing environments.

• Journal of KIISE:Software and Applications
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• v.33 no.6
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• pp.564-573
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• 2006

Temporal information plays an important role in natural language processing (NLP) applications such as information extraction, discourse analysis, automatic summarization, and question-answering. In the topic detection and tracking (TDT) area, the temporal information often used is the publication date of a message, which is readily available but limited in its usefulness. We developed a relatively simple NLP method of extracting temporal information from Korean news articles, with the goal of improving performance of TDT tasks. To extract temporal information, we make use of finite state automata and a lexicon containing time-revealing vocabulary. Extracted information is converted into a canonicalized representation of a time point or a time duration. We first evaluated the extraction and canonicalization methods for their accuracy and investigated on the extent to which temporal information extracted as such can help TDT tasks. The experimental results show that time information extracted from text indeed helps improve both precision and recall significantly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.45-56
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• 2007

Automatic tracking of vehicles is important to accurately estimate the traffic information including vehicle speeds in video-based traffic measurement systems. Because of the limited field of view, the range of visual tracking with a single camera is restricted. In order to enlarge the tracking range for better chance of monitoring the vehicle behaviors, a tracking with consecutive multiple video sequences is necessary. This parer proposes a carefully designed rule-based vehicle racking scheme and apply it for the tracking for two well synchronized video sequences. In the scheme, almost all possible cases that can appear in the video-based vehicle tracking are considered to make rules. Also, the rule based scheme is augmented with Kalman filter. The result of tracking can be successfully used to collect data such as temporal variation of vehicle speed and behavior of individual vehicle behaviors in the enlarged tracking region.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.47-56
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• 2015

In the multi-sensor system, sensor registration errors such as a sensor bias must be corrected so that the individual sensor data are expressed in a common reference frame. If registration process is not properly executed, large tracking errors or formation of multiple track on the same target can be occured. Especially for launch vehicle tracking system, each multiple observation lies on the same reference frame and then fused trajectory can be the best track for slaving data. Hence, this paper describes an on-line bias estimation/correction and asynchronous sensor fusion for launch vehicle tracking. The bias estimation architecture is designed based on pseudo bias measurement which derived from error observation between GPS and radar measurements. Then, asynchronous sensor fusion is adapted to enhance tracking performance.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.178-183
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• 2024

This study introduces an enhanced sound source localization technique, bolstered by a data-driven deep learning approach, to improve the precision and accuracy of direction of arrival estimation. Focused on refining Time Difference Of Arrival (TDOA) based sound source localization, the research hinges on accurately estimating TDOA from cross-correlation functions. Accurately estimating the TDOA still remains a limitation in this research field because the measured value from actual microphones are mixed with a lot of noise. Additionally, the digitization process of acoustic signals introduces quantization errors, associated with the sampling frequency of the measurement system, that limit the precision of TDOA estimation. A deep learning-based approach is designed to overcome these limitations in TDOA accuracy and precision. To validate the method, we conduct comprehensive evaluations using both two and three-microphone array configurations. Moreover, the feasibility and real-world applicability of the suggested method are further substantiated through experiments conducted in an anechoic chamber.

• 한국ITS학회:학술대회논문집
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• 2010.05a
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• pp.184-187
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• 2010

RFID 기술은 각 사물에 전자태그를 부착하고, 사물의 고유 ID를 무선으로 인식하여, 해당 정보를 수집, 저장, 추적함으로써 사물에 대한 측위, 원거리 관리 및 사물 간 정보교환 등의 서비스를 제공하는 기술이다. RFID의 응용 분야의 하나로 전자태그가 부착되어 있는 대상의 위치를 실시간으로 파악하고 확인할 수 있는 RTLS(Real Time Locating Systems) 기술이 새로이 부각되고 있다. 본 논문에서는 AP의 RSSI(Received Signal Strength Indication)를 이용해 데이터의 정확도를 위해 약 30회의 위치 추정을 통한 위치 추정의 정확도를 알아보고 스무딩을 통한 측정 거리의 오차를 확인했다. AP의 RSSI를 통한 위치추정은 AP가 설치된 건물내의 실내환경에서 이루어졌으며, 비교적 정확한 약 3m의 오차를 보였고, 필터링을 통한 교통 추정값은 그보다 약 0.5~1m 향상된 성능을 보였다.