• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.364-366
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• 2006

본 논문에서는 인간의 눈 움직임이 반영된 물체 추적 기능을 모방하여 CCD 카메라를 통하여 실시간으로 입력되는 영상 데이터로부터 특징기반 정합방법을 응용하여 움직임 정보를 추출한 후, 팬-틸트(pan-tilt) 기능의 하드웨어를 제어하여 실시간으로 이동하는 물체를 효율적으로 추적하는 시스템을 제안하였다. 기존의 연구들에서는 주로 물체의 색상값을 이용하여 추적이 이루어지므로 조명이나 카메라의 변화에 따라 이동 물체를 놓치거나 유사한 색의 다른 물체를 잘못 추적하는 문제가 있었다. 이러한 문제점을 해결하기 위하여 측정기반의 정합을 응용하여 이동하는 카메라에서 이동물체를 추출하고 이 이동 물체의 좌표를 이동하여 팬-틸트 하드웨어를 제어하여 추적을 수행하였다. 실험 결과 본 시스템은 움직이는 물체를 감지해서 팬-틸트 하드웨어를 올바르게 제어하며 카메라의 움직임을 보정해가며 전체적으로 움직이는 영상 내에서 실제 움직이는 물체를 일관성 있게 추적하는 만족스러운 결과를 보인다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.180-183
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• 2010

본 연구에서는 개선된 영역기반의 패턴매칭 기법을 사용하여 이동물체의 탐색과 검출을 수행하였다. 시간에 따라 변화하는 이동물체의 안정된 추적을 위해 매 영상 프레임마다 이동물체의 윤곽선을 탐지하여 다음 영상에서의 템플릿으로 사용하기 위해 갱신하였으며, 패턴매칭의 연산속도 향상을 위해 패턴 정합률에 따라 영상을 다른 비율로 압축하여 추적하는 방법을 제안하였다. 기존의 영상파일을 사용하여 시뮬레이션 한 결과 이동물체의 검출과 추적에 양호한 동작을 보여주었으며 제안된 방법의 실시간 동작 가능성을 조사하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1461-1463
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• 2015

본 논문에서는 이동 객체를 추적하기 위해 HSI 색상 모델 기반으로 하는 파티클 필터를 이용하고, 차영상을 통해 추적하고자 하는 객체의 중심점을 보완하는 방법을 제안한다. 색상 모델 기반 파티클 필터로 이동 객체를 추적했을 때, 객체의 색 혼합도의 문제로 객체의 중심과 파티클들의 분포에 대한 정확성이 떨어져 추적의 어려움이 있다. 이 문제를 해결하기 위해 각 프레임마다 차영상을 만들어 이동객체의 중심점을 찾고, 파티클 필터로 추적한 중심점과 비교하여 객체의 중심점을 보완해 추적에 대한 정확성을 높일 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.396-397
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• 2015

본 논문에서는 이동 물체의 연속 위치 추적을 위한 무선 저전력 기저대역 모뎀을 설계 및 구현하였다. 설계된 모뎀은 단일 하드웨어로 16칩 및 32칩 대역확산을 통해 900MHz 대역 및 2.4GHz 대역을 동시에 지원하며, 250Kbps 이하 가변전송률 전송을 통해 다양한 통달거리 지원이 가능하다. FPGA 기반 구현 결과, 설계된 기저대역 모뎀은 8,010 Slice, 20,672 Slice LUT, 25,512 Flip Flop, 18Kb Block RAM으로 구성되었음을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.319-322
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• 2013

본 연구에서는 이동 객체를 컬러기반에서 추적하는데 있어 주변 환경 변화와 추적중인 객체 색상이 유사한 물체가 존재할 경우 보다 안정적으로 추적할 수 있는 방법을 제시한다. 백그라운드 차영상과 모폴로지 연산을 통하여 이동 객체를 검출하고, 매 프레임마다 발생하는 밝기 및 주변 환경의 영향을 고려하여 기존의 CamShift 알고리즘을 보완하였다. 추적 물체와 색상이 비슷한 주변 물체가 존재할 경우 개선된 CamShift는 불안정한 추적을 보여주었는데 이를 해결하기 위해 Optical Flow기반의 KLT 알고리즘과 병합하는 방법을 제시하였다. 실험 결과를 통해 제안된 추적 방법은 기존의 단점을 보완하였으며 추적성능이 개선됨을 확인하였다.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2109-2119
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• 2001

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-2 bit-steam is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algorithm has two important steps, namely the motion vectors extraction from MPEG-2 bit-stream and the watershed algorithm. The algorithm extracts objects using user\`s assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object, the user can intervene to correct the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracts processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tacking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask, and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-2 bit-stream to the object-based MPEG-4 input.

• 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 Society for Marine Environment & Energy
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• v.16 no.1
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• pp.1-8
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• 2013

This study focuses on a ship detection and tracking method using Frequency Modulated Continuous Wave (FMCW) radar used for horizontal surveillance. In general, FMCW radar can play an important role in maritime surveillance, because it has many advantages such as low warm-up time, low power consumption, and its all weather performance. In this paper, we introduce an effective method for data and signal processing of ship's detecting and tracking using the X-band radar. Ships information was extracted using an image-based processing method such as the land masking and morphological filtering with a threshold for a cycle data merged from raw data (spoke data). After that, ships was tracked using search-window that is ship's expected rectangle area in the next frame considering expected maximum speed (19 kts) and interval time (5 sec). By using this method, the tracking results for most of the moving object tracking was successful and those results were compared with AIS (Automatic Identification System) for ships position. Therefore, it can be said that the practical application of this detection and tracking method using FMCW radar improve the maritime safety as well as expand the surveillance coverage cost-effectively. Algorithm improvements are required for an enhancement of small ship detection and tracking technique in the future.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.