• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.5
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• pp.42-51
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection, especially active shadows resulted from moving vehicles. In this paper, a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98% in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic parameters concerning traffic flow is obtained to describe the load of each lane.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.161-170
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

• Journal of Fashion Business
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• v.16 no.4
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• pp.29-45
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• 2012

The purpose of this study is for providing not only the latest design technique trend for zero waste fashion, but information about creative fashion design education through eco-fashion industry trend in globally and domestic which is focusing on eco-fashion labelling. The research were processed with literature related eco, sustainable, green fashion books, former articles, newspapers, and web sites. The results as follows; The certification about eco-fashion product is moving to 'Life Cycle Assessment' from focused on primary process like material, finishing, dyeing. Especially simplicity of process means reducing the wastes. And fabric wastage for adult outwear was estimated 15% percent of total fabric used in general design studios. Three cases for Zero waste fashion were as follows; First, Jigsaw puzzle by Timo Rissane and Mark Liu were different zero waste methods, but the result was same. Rissene's method was based on traditional cutting like 'cut and sew' but traditional cutting can lead to design that have an abundance of fabric and drape. Jigsaw of Rissene was approached with description a pattern-cutting technique in which all piece interlock with each other generating no waste from design production. Another Jigsaw by Liu was related with innovative textile design. DTP makes the possibilities for zero waste garment production almost endless. The dress intricately cut from 10 pieces, wastes none of the fabric required to make it. Second, Subtraction Cutting by Julian Roberts provides unexpected fluid, organic forms and zero waste fabric. Utilizing Roberts plug(tunnel) technique enables any part of the garment that is removed for fit or aesthetics to be reincorporated into the design of garment. Third was 'Bio Couture' by Suzanne Lee. She has created garments from cellulose bacteria which grow in a bathtub using only green methods addressing in such as way ecological issues and exploring the future of fashion design in conjunction with technology.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.63-63
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• 2003

Purpose: Planning target volume (PTV) for tumors in abdomen or thorax includes enough margin for breathing-related movement of tumor volumes during treatment. We developed a simple and handy method, which can reduce PTV margins in patients with moving tumors, respiratory motion reduction device system (RMRDs). Materials and Methods: The patients clinical database was structured for moving tumor patients and patient setup error measurement and immobilization device effects were investigated. The system is composed of the respiratory motion reduction device utilized in prone position and abdominal presser (strip device) utilized in the supine position, moving phantom and the analysis program, which enables the analysis on patients setup reproducibility. It was tested for analyzing the diaphragm movement and CT volume differences from patients with RMRDs, the magnitude of PTV margin was determined and dose volume histogram (DVH) was computed using a treatment planning software. Dose to normal tissue between patients with RMRDs and without RMRDs was analyzed by comparing the fraction of the normal liver receiving to 50% of the isocenter dose(TD50). Results: In case of utilizing RMRDs, which was personally developed in our hospital, the value was reduced to $5pm1.4 mm$, and in case of which the belt immobilization device was utilized, the value was reduced to 3$pm$0.9 mm. Also in case of which the strip device was utilized, the value was proven to reduce to $4pm.3 mm$0. As a result of analyzing the TD50 is irradiated in DVH according to the radiation treatment planning, the usage of the respiratory motion reduction device can create the reduce of 30% to the maximum. Also by obtaining the digital image, the function of comparison between the standard image, automated external contour subtraction, and etc were utilized to develop patients setup reproducibility analysis program that can evaluate the change in the patients setup. Conclusion: Internal organ motion due to breathing can be reduced using RMRDs, which is simple and easy to use in clinical setting. It can reduce the organ motion-related PTV margin, thereby decrease volume of the irradiated normal tissue.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1191-1194
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• 2004

We describe the development of an interactive aerobic training system using vision-based motion capture and multimedia technology. Unlike the traditional one-way aerobic training on TV, the proposed system allows the virtual trainer to observe and interact with the user in real-time. The system is composed of a web camera connected to a PC watching the user moves. First, the animated character on the screen makes a move, and then instructs the user to follow its movement. The system applies a robust statistical background subtraction method to extract a silhouette of the moving user from the captured video. Subsequently, principal body parts of the extracted silhouette are located using model-based approach. The motion of these body parts is then analyzed and compared with the motion of the animated character. The system provides audio feedback to the user according to the result of the motion comparison. All the animation and video processing run in real-time on a PC-based system with consumer-type camera. This proposed system is a good example of applying vision algorithms and multimedia technology for intelligent interactive home entertainment systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.88-94
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• 2009

This paper proposes real time object detection and tracking algorithm that can be applied to security and supervisory system field. A proposed system is devide into object detection phase and object tracking phase. In object detection, we suggest Adaptive background subtraction method and Adaptive block based model which are advanced motion detecting methods to detect exact object motions. In object tracking, we design a multiple vehicle tracking system based on Kalman filtering. As a result of experiment, motion of moving object can be estimated. the result of tracking multipul object was not lost and object was tracked correctly. Also, we obtained improved result from long range detection and tracking.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.387-391
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• 2008

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.